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We selected Symptom and pathology datasets indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic
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We selected Epidemiology datasets that are indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic.
Data Types:
  • Collection
We selected Vaccine research datasets indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic
Data Types:
  • Collection
We selected datasets that are indexed by the Mendeley Data Search engine on the 2019-present COVID-19 / Coronavirus pandemic. The aim was to make it easier to find potentially relevant datasets for this specific topic
Data Types:
  • Collection
this Data reveals all results founded in this research paper
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Palynomorph assemblages and palynofacies analysis have been performed on several core samples from the Devonian–Carboniferous deposits identified in five wells located in the eastern part of the Moesian Platform. The investigated sections include, in ascending stratigraphic order, the Ţăndărei, Smirna, Călăraşi and Vlaşin formations. Based on stratigraphic distribution of key taxa identified (miospores, chitinozoans, acritarchs), seven biozone intervals (four for Devonian and three for Carboniferous) have been recognized. The oldest samples were dated as being part of the micrornatus-newportense (MN) – lower part of breconensis-zavallatus (BZ) interval zones (early Devonian), while the younger ones are assigned to the kosankei-varioreticulatus (KV) – nobilis-junior (NJ) interval zones (late Carboniferous). Palynofacies observations suggest a more distal depositional environment during the period between Lochkovian and Pragian times, followed by some proximal/fluvio-deltaic conditions in Emsian–early Eifelian (the top of Ţăndărei Formation). The upper Tournaisian to Serpukhovian sedimentary rocks of the Călăraşi and lower part of Vlaşin formations were deposited in inner neritic environments. Mud-dominated dysoxic/anoxic conditions prevailed in the Bashkirian, which were quickly succeeded by a deltaic deposition and oxidizing environments which persisted up to Moscovian. The lower Devonian terrestrial palynoflora is dominated by trilete spores which belong to the lowland vegetation of a non-forest mire palaeoecological group. The Carboniferous deposits yielded only terrestrial palynomorphs of various types of arborescent and herbaceous lycopsids and ferns, suggesting different habitats such as non-flooded wetlands or swamps within coastal plain and continental interiors. These assemblages of Carboniferous miospores are an indication of the neutral-humid climatic conditions which existed at the time of deposition.
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There is a detailed Readme.pdf in the files for the informations about the dataset. The main purpose is providing a dataset for the vibration behavior of a robot manipulator system under the control input of model-associative vibration control (MAVC) prodecure. Velocity profile is shown as [∗,𝑡𝑐𝑜𝑛,𝑡𝑑𝑒𝑐,𝑡𝑚] in study. In the case studies for both simulations and experiments, the parameters are varied as follows; 𝑡𝑐𝑜𝑛 can be valued as 0, 𝑡1ℎ or 2𝑡1ℎ, 𝑡𝑑𝑒𝑐 can be valued as 𝑡1ℎ,2𝑡1ℎ,3𝑡1ℎ,4𝑡1ℎ or 5𝑡1ℎ and 𝑡𝑚 can be valued as 1 or 1.5 seconds for corresponded 90 or 135 angular displacements. Thus thirty different velocity profiles are produced with aim to performed on system. Cases are invastigated with and without performing the MAVC procedure. Than the robot manipulator is examined for both unloaded and loaded cases, therefore total one hundred twenty cases are occured. More details can be found in related study.
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Western blots and soft agar images
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Supplementary Data. Includes Excel data tables for ages and shapefiles for ages, geomorphology and ice-sheet reconstruction.
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Non-marginal (average) AWARE CFs and WSI CFs: We provide a shapefile, CSV file and KML file of the average AWARE characterization factors (CFs) based on the marginal AWARE CFs from Boulay et al. (2018). We also provide it together with average WSI factors from Pfister and Bayer (2014), since based on the UNEP SETAC recommendation, AWARE should be used together with an alternative scarcity method to test sensitivities (Jolliet et al. 2018). The XLS version of the average AWARE CFs is available from the original publication: Pfister S, Scherer L, Buxmann K (2020) Water scarcity footprint of hydropower based on a seasonal approach - Global assessment with sensitivities of model assumptions tested on specific cases. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2020.138188 DATA structure: The CSV files lists CFs for each month (01 to 12) and each methods: AWARE_01 stands for original marginal AWARE CFs of January, AWARE_a_01 represents the newly calculated average AWARE CFs for January, WSI_01 are the marginal WSI CFs for January and WSI_AVG_01 the average WSI CFs for January. The CSV file can be linked to WaterGAP watersheds based on the "BAS34S_ID" . The WaterGAP shapefile is e.g. available at http://www.wulca-waterlca.org/aware.html. The Shapefile and KML file follows the same order but are already linked to the watershed shapefile.
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  • Geospatial Data
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