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990 results for “quantification”
Experimental dataset: stationary images for digital image correlation uncertainty quantification
<div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>-------------------------------------------------------------------------------- <strong>SUMMARY</strong> ---------------------------------------------------------------------------</div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div> </div> <div>Stereo-DIC 5 MPx system was used to capture sets of stationary images for quantification of DIC uncertainties.</div> <div> </div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>-------------------------------------------------------------------------------- <strong>FOLDERS </strong>---------------------------------------------------------------------------</div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div> </div> <div><strong>Image sets:</strong> </div> <div> </div> <div><strong>Set 1: </strong>100 stationary images with cross polarisation to reduce effect of specular reflection. Test sample clamped in the clamps of a uniaxial tensile test bench.</div> <div><strong>Set 2: </strong>Same as set 1, but test sample unclamped at the bottom, displaced by 1 mm vertically. Meant to introduce rigid body motion into teh stationary images. </div> <div>For investigation of the impact of cross-polarisation: image gradients made similar as much as possible by adjusting exposure time and apetrture. </div> <div><strong>Set 3:</strong> With cross polarisation - 100 stationary images.</div> <div><strong>Set 4:</strong> Without cross polarisation - 100 stationary images.</div> <div> </div> <div>Images for stereo calibration:</div> <div> </div> <div><strong>Calib_sets_1_2: </strong>Calibration images for sets 1 and 2 mentioned above </div> <div><strong>Calib_sets_3:</strong> Calibration images for set 3 mentioned above </div> <div><strong>Calib_sets_4: </strong>Calibration images for set 4 mentioned above </div> <div> </div> <div>----------------------------------------------------------------------------------------------------------------------------------------------------------------------</div> <div>------------------------------------------------------------------------ <strong>SUPPORTING NINFORMATION </strong>--------------------------------------------------------------------</div> <div>---------------------------------------------------------------------------------------------------------------------------------------------------------------------- </div> <div> </div> <div>Image folder for each set contains an *.xaml file with image capture settings.</div> <div>Each calibration image folder contains a *.caldat file with intrinsic and extrinsic stereo camera parameters identified by MatchID 2024.2 DIC package.</div>
Mobile MAX-DOAS measurements for emission quantifications and source analysis of NO2, HCHO and HONO during Chengdu 2021 FISU World University Games
<p>The shared data includes the spatial distribution of NO2, HCHO and HONO measured by moving MAX-DOAS during the Chengdu 2021 FISU World University Games</p>
Quantitative real-time PCR assays Q2 for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates
<p>These are the data behind figures 2 to 7 in the paper: Brink AM, Kremp A and Gorokhova E (2024) Quantitative real-time PCR assays for species-specific detection and quantification of Baltic Sea spring bloom dinoflagellates. Front. Microbiol. 15:1421101. doi: 10.3389/fmicb.2024.1421101</p>
Label-Free Quantification (LFQ) LC-MS Data for the Profiling of Domain-specific VCP/p97 Interactions in Living Cells
<p>This deposit includes LFQ LC-MS data for tandem-IP samples from VCP-L278AbK and VCP-D592AbK crosslinking experiments, their VCP-L278BocK and VCP-D592BocK controls, and SpectroMine output files.</p>
Data Wood Quantification From Ortho
<p>Data for wood detection and quantification method.</p> <p>https://github.com/janbertoo/wood_quantification_from_ortho</p>
Supplementary material - Sandy soil spots in northwestern Paraná: approaches for identification and quantification
<p>The file contains the Supplementary Table from Sandy soil spots in northwestern Paraná: approaches for identification and quantification and the Tiff with the sand percentage. </p>
Joint multi-field T1 quantification for fast field-cycling MRI
<p>Phantom and in-vivo data for the publication.</p>
Data for: Real-time Radial Tagging for Quantification of Left Ventricular Torsion
<p>Magnetic Resonance Imaging measurement and simulation data used in our research about ‘Real-time Radial Tagging for Quantification of Left Ventricular Torsion'.</p>
Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software.
<p>We uploaded the complete database of the manuscript: Grassi R, Cappabianca S, Urraro F, Feragalli B, Montanelli A, Patelli G, Granata V, Giacobbe G, Russo GM, Grillo A, De Lisio A, Paura C, Clemente A, Gagliardi G, Magliocchetti S, Cozzi D, Fusco R, Belfiore MP, Grassi R, Miele V. Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software. Int J Environ Res Public Health. 2020 Sep 22;17(18):6914. doi: 10.3390/ijerph17186914. PMID: 32971756; PMCID: PMC7558768.</p>
Fig. 1 in Quantification of Predation on the Dung BeetleCanthidium cupreum(Blanchard) (Coleoptera: Scarabaeidae: Scarabaeinae) byLeistotrophus versicolor(Gravenhorst) (Coleoptera: Staphylinidae)
Fig. 1. Adult Leistotrophus versicolor preying on Canthidium cupreum. Illustration by Jorge Ali Salas.
Quantification of methane emissions from indoor-fed Fogera dairy cows using laser methane detector
<p>Using the laser methane detector (LMD) in a respiration chamber (Linze Grassland Agriculture Trial Station, Lanzhou University, Gansu Province, China).</p>
Quantification of methane emissions from indoor-fed Fogera dairy cows using laser methane detector
<p>Using the laser methane detector to measure the methane emissions from Fogera dairy cows (Andassa Livestock Research Center, Amhara Region Agricultural Research Institute, Ethiopia).</p>
A framework for the quantification of soundscape diversity using Hill numbers
<p>This is the data underlying the case study and supplementary material described in Luypaert et al. (2021): A framework for the quantification of soundscape diversity using Hill numbers. </p>
ALL processed data of quantification of Total, viable and VC population
<p>Processed data set of qPCR, PMA-qPCR and agar enumeration of the article. These data are sorted according to the D2O concentration used (0%, 25%, 50% or 75%), and according to the incubation time</p>
Laser Ablation Inductively Coupled Plasma Mass Spectrometric Quantification of Isotope Trace Elements in Human Carcinoma Tissue - Stochastic Dynamics and Theoretical Analysis (SUPPORTING INFORMATION)
<p>Supporting information file of publication [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4334866]. </p>
Quantification data for article entitled "ATG9 vesicles comprise the seed membrane of mammalian autophagosomes"
<p>Membrane fractionation, immunoprecipitation, and <em>in vitro</em> experiment densitometric quantification datasheets for quantified data presented in the research article entitled "ATG9 vesicles comprise the seed membrane of mammalian autophagosomes". Membrane fractions (Figures 3, 4, S4, and S5) were from WT cells (starvation + bafiomycin A1 and basal conditions), ATG2 DKO cells, FIP200 KO cells, ATG9A KO cells, ATG3 KO cells, and ATG4 QKO cells (all KO cells under basal conditions). Immunoprecipitations (Figures 6 and S5) were from WT cells (starvation + bafiomycin A1) and ATG2 DKO cells (basal). Guanidine hydrochloride (GdnHCl) sequential immunoprecipitations (Figure 6) were from WT cells (starvation + bafiomycin A1). <em>In vitro</em> experiments (Figure S5) were using recombinant proteins on reconstituted liposomes.</p>
Data Archive for "Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification"
<p>This repository contains the training data and pretrained models for the paper "Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification".</p> <p>To use the data, clone the repository at <a href="https://github.com/MeteoSwiss/ldcast">https://github.com/MeteoSwiss/ldcast</a>. Unzip the files as follows:</p> <ul> <li>Demo files "ldcast-demo-20210622.zip" to the "data" directory</li> <li>Training and evaluation data archive "ldcast-datasets.zip" to the "data" directory</li> <li>Pretrained model archive "models-genforecast.zip" to the "models" directory</li> </ul>
Training material for the mapping and quantification of single-cell ATAC-seq 10X Datasets
<p>The data provided here is part of the Galaxy Training Network tutorial that analyses 10x genomics single-cell ATAC-seq data from the 10x platform. </p> <p>Due to time constraints during training, the datasets were subsampled to reads that map to chrY.</p> <p>The 10x Genomics Datasets follow the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution</a> license.</p>
Figure 3 in Quantification of underwater calling and foraging activities in the African clawed frog Xenopus laevis
Figure 3. Effects of moonlight intensity, along with lunar cycle, on A) Vocal activity, B) Foraging activity as estimated as the number of animals captured in food baited traps and C) sex ratio of captures (number of males/ total number of individuals), with points for observed values, and 95% confidence interval around the mean estimated from the best model.
Figure 2 in Quantification of underwater calling and foraging activities in the African clawed frog Xenopus laevis
Figure 2. Variations of A) Vocal activity, B) Foraging activity as estimated as the number of animals captured in food baited traps and C) sex ratio of captures (number of males/ total number of individuals), during the study period, according to date and lunar cycle with points for observed values, and 95% confidence interval around the mean estimated from the best model.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.