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8,547 results for “Characterization”
The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons
<p>This project contains the annotated transcriptomes in GTF format used in the manuscript "The Human Developing Cerebral Cortex Is Characterized by an Elevated De Novo Expression of Long Noncoding RNAs in Excitatory Neurons" DOI: <a href="https://doi.org/10.1093/molbev/msae123">https://doi.org/10.1093/molbev/msae123</a></p>
Three-Dimensional Characterization of Deformation-induced Damage in Dual Phase Steel using Deep Learning
<p>High performance sheet metals with a multi-phase microstructure suffer from deformation induced damage formation during forming in the constituent phases but importantly also where these intersect. To capture damage in terms of the physical processes in three dimensions (3D) and its stochastic nature during deformation, two challenges remain to be tackled: First, bridging high resolution analysis towards large scales to consider statistical data and, second, characterising in 3D with a resolution appropriate for sub-micron sized voids at a large scale. Here, we present how this can be achieved using panoramic scanning electron microscopy (SEM), metallographic serial sectioning, and deep-learning assisted automatic image analysis. This brings together the 3D evolution of active damage mechanisms with volumetric and environmental information for thousands of individual damage sites. We also assess potential surface preparation artefacts in 2D analyses. Overall, we find that for the material considered here, a dual phase (DP800) steel, martensite cracking is the dominant but not sole origin of deformation induced damage and that for a quantitative comparison of damage density, metallographic preparation can induce additional surface damage density far exceeding what is commonly induced between uniaxial straining steps.</p> <p>https://doi.org/10.1016/j.matdes.2023.112108</p>
Reproduction package for the paper "Exploring the directly imaged HD 1160 system through spectroscopic characterization and high-cadence variability monitoring"
<p>This is a basic reproduction package for the paper <a href="https://doi.org/10.1093/mnras/stae1315">"Exploring the directly imaged HD 1160 system through spectroscopic characterization and high-cadence variability monitoring" by Sutlieff et al. (2024)</a>. It aims to provide the most important data products to check and reproduce the main results of the paper.</p>
Data for a publication "Amino-Modified ZIF-8 for Enhanced CO2 Capture: Synthesis, Characterization and Performance Evaluation"
<p>Data for a publication "Amino-Modified ZIF-8 for Enhanced CO2 Capture: Synthesis, Characterization and Performance Evaluation".</p> <p><strong>Versions of dataset:</strong></p> <p><strong><span>V1: </span></strong><span>First dataset regarding the data used in the article.</span></p> <p><strong><span>V2:</span></strong><span> The dataset </span><span>was newly reorganized</span><span>, containing the </span><span>data,</span><span> that </span><span>were used</span><span> for the published article. </span><span>More information can be found</span><span> in the README file.</span></p> <p><strong>Article abstract</strong></p> <p>The urgent need for sustainable and innovative approaches to mitigate the increasing levels of atmospheric CO<sub>2</sub> necessitates the development of efficient methods for its removal. In this study, we focus on the new, innovative approach for synthesis and functionalization of metal-organic framework (MOF) ZIF-8 in one step at room temperature to enhance its capacity for CO<sub>2</sub> capture. Specifically, we investigated the impact of four amino-compounds, namely tetraethylenepentamine (TEPA), hexadecylamine (HDA), <a title="Learn more about ethanolamine from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/chemical-engineering/ethanolamine">ethanolamine</a> (ELA), and cyclopropylamine (CPA), on the <a title="Learn more about chemical structure from ScienceDirect's AI-generated Topic Pages" href="https://www.sciencedirect.com/topics/materials-science/structure-composition">chemical structure</a>, size, surface area and porosity, and CO<sub>2</sub> capturing of ZIF-8 powder. By varying concentrations of the amino-compounds, we examined their influence on the ZIF-8 properties. Our findings demonstrate that each amino-compound and its respective concentration exhibit distinct effects on the characteristics of ZIF-8. Notably, the ZIF-8 sample functionalized with the highest presented concentration of TEPA exhibited significant improvement in CO<sub>2</sub> trapping efficiency, with a 33.3% enhancement. Moreover, least concentrated samples with added HDA or CPA demonstrated notable improvements with enhancements of 46.6% and 18.6%, respectively. These results highlight the potential of simple synthesis and functionalization techniques for MOFs in enhancing their CO<sub>2</sub> capture capabilities. The findings from this study offer new opportunities for the development of strategies to mitigate CO<sub>2</sub> emissions using MOFs.</p>
Minimal data set for: Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend
<p>This minimal data set presents the values behind the means and standard deviation for the publication entitled: "Air-liquid interface exposure of A549 human lung cells to characterize the hazard potential of a gaseous bio-hybrid fuel blend"</p>
Multiscale analysis of triglycerides with X-ray scattering: Implementing a shape-dependent model for CNP characterization - Supporting Dataset
<p>This dataset contains the files used to substantiate the outcomes of the publication "<em>Multiscale analysis of triglycerides with X-ray scattering: Implementing a shape-dependent model for CNP characterization</em> <em>" </em></p> <p>The dataset includes:</p> <ul> <li>X-ray scattering profiles - in absolute units</li> <li>Images used to measure CNP distributions</li> </ul> <p>Relevant abbreviations: </p> <ul> <li>SSS - Tristearin</li> <li>OOO - Triolein</li> <li>FHRO - Fully Hydrogenated Rapeseed Oil</li> <li>HOSO - High Oleic Sunflower Oil</li> </ul>
Identification and Functional Characterization of an Alternative Cancer-derived PD-L1 Isoform (supplemental data)
<p>The enclosed files contain all of the supplemental data from: Identification and Functional Characterization of an Alternative Cancer-derived PD-L1 Isoform. The files include the complete tables in CSV-formatted files.</p>
Data for "Vertical characterization of highly oxygenated molecules (HOMs) below and above a boreal forest canopy"
<p>This excel file consists of the data been analyzed in the manuscript "Vertical characterization of highly oxygenated molecules (HOMs) below and above a boreal forest canopy". For more details, please contact the author (qiaozhi.zha@helsinki.fi). </p>
Characterizing the gamma-ray variability of the brightest flat spectrum radio quasars observed with the Fermi LAT
<p>The FITS files contain light curves (prefix "lc"), spectral energy distributions (prefix "sed") and best-fit parameters for the whole region of interest (prefix "bestfit_roi") for the gamma-ray analyses of the six brightest flat spectrum radio quasars observed over 9.5 years with the Fermi Large Area Telescope (LAT). The file names also indicate the considered binning (weekly, daily, orbit, sub-orbital) and the considered time range in MJD.<br> The data products have been generated using the fermipy software, please see the documentation for further explanations of the columns provided in these files: <a href="https://fermipy.readthedocs.io/en/latest/">https://fermipy.readthedocs.io/en/latest/</a></p> <p>The analysis catalog are described in detail in the accompanying paper, which is submitted for publication in the Astrophysical Journal. The preprint of the submitted manuscript can be found here: <a href="https://arxiv.org/abs/1902.02291">https://arxiv.org/abs/1902.02291</a></p> <p>Additionally, the code for high level analysis including the light curves and the gamma-ray absorption in the broad line region can be found on github: <a href="https://github.com/me-manu/GaRLiC">https://github.com/me-manu/GaRLiC </a>and <a href="https://github.com/me-manu/blrabsorption">https://github.com/me-manu/blrabsorption</a></p> <p> </p>
Discovery and characterization of pyridine and furan substituted ligands of choline acetyltransferase
<p><span>This repository contains datasets for the manuscript "Discovery and characterization of pyridine and furan substituted ligands of choline acetyltransferase"</span></p> <ul> <li><span>Data set of 1.4 million compounds used for virtual screening are freely available at </span><span><a href="https://vitasmlab.biz/downloads"><span>https://vitasmlab.biz/downloads</span></a></span><span>. Vina-MPI used for the virtual screening protocol is freely available at </span><span><a href="https://github.com/mokarrom/mpi-vina"><span>https://github.com/mokarrom/mpi-vina</span></a></span><span>. </span></li> <li><span>The docking pose and docking score for the screened library with Vina-MPI is available in PDBQT format with their docking scores in the folder “vitas_virtual_screening_800K”.</span></li> <li><span>Selected 5958 compounds from the virtual screening are given as PDBQT with docking scores in folder “top_5K_hits”.</span></li> <li><span>Re-docked docking score (Top_5K_re_docking.sdf) and MMGBSA (Top_250_MMGBSA.sdf) calculation are also available with the structures in SDF format.</span></li> </ul>
Data on the material characterization of cast and additively manufactured IN939 subjected to room-temperature low-cycle fatigue load
<p>The original data to the research paper termed "Room-temperature low-cycle fatigue behaviour of cast and additively manufactured IN939 superalloy" are enclosed. Two specimen orientations of L-PBF IN939 - horizontal and vertical, and two thermodynamical states - without subsequent heat treatment (non-treated) and standard aged according to Delargy et al., 1986, were investigated. The paper concerns the low-cycle fatigue performance of cast and additively manufactured IN939 superalloy. It brings a comprehensive account on the damage and deformation behaviour of the tested alloy, combining the test analyses with high-resolution SEM and TEM observations.</p>
Accelerating Quantum Emitter Characterization with Latent Neural Ordinary Differential Equations
<p>Datasets used in 'Accelerating Quantum Emitter Characterization with Latent Neural Ordinary Differential Equations', published in AI4Mat-NeurIPS-2024.</p> <ul> <li>pcfs_g2_2d_n50000_20240623_nstage200_maxdelay66_.h5 was used for inputs and predictions in Fig. 1 and Fig. 2</li> <li>pcfs_g2_2d_n50000_20240820_nstage100_maxdelay120.h5 was used for inputs and predictions in Fig. 3</li> </ul> <p> </p>
Characterization of Metabolism Associated with Outcomes in Severe Acute Pancreatitis: Insights from Serum Metabolomic Analysis
<p>1H NMR spectra data of SAP patients (Survivors/ Non-survivors). The spectra were binned as 0.02 ppm spectral buckets. The chemical shift regions corresponding to the water region and TSP were excluded to avoid spectral interference. This dataset was used for the metabolomics related study to highlight the dysregulation of metabolites in the study group.</p> <p> </p>
Morphological and physical chemical characterization of main agricultural plastics articles used for protected cultivation systems during ageing in fields, and collection practices
<p>This dataset includes data generated upon the implementation of the ST 1.2.1 "Analysis of degradation and fragmentation of AP and transfer of MNP to soil". The activities dealt with the study of degradation and fragmentation from weathering and agricultural practices of conventional and biodegradable AP relevant for transfer of MNP to soil (during both use and end of life). In particular, the experimental data refer to characterization of biodegradable mulch films, pristine (coded M-BIO0) or subjected to photo-oxidative weathering (M-BIO192), as well as the same samples buried in soil for varying time periods, up to 353 days. The folders included contain gel permeation chromatography (GPC) and Matrix-assisted Laser Desorption Ionization (MALDI-TOF) data, which account for the change in film molecular weight upon soil burial. Furthermore, Differential Scanning Calorimetry (DSC) data and Scanning Electron Microscopy (SEM) and Water Contact Angle (WCA) images of some selected samples are also provided. The folder named MS RAW FILES.zip includes all the mass spectrometry raw data.</p>
Characterizing cell-type spatial relationships across length scales in spatially resolved omics data: data repository
<h1>CRAWDAD</h1> <p>Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we develop CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package with source code and additional documentation at https://jef.works/CRAWDAD/.</p> <p>During CRAWDAD's development, we generated simulated datasets and new cell-type annotations for human spleen data, provided here. The external datasets such as the mouse cerebellum, mouse embryo, mouse brain, and human breast cancer data used in the paper can be found in their original publication. See more information in CRAWDAD's data availability statement.</p> <h2>Simulated Datasets</h2> <ul> <li>sim.csv: the simulated data. Used in Figure 1 b-g, Supplementary Figure 1 a-c, and Supplementary Figure 9 a-b.</li> <li>ext_sim.csv: the extended simulated data. Used in Supplementary Figure 1 d-f.</li> <li>null_sim_visualization.csv: the null simulated data. Used to generate the plots Supplementary Figure 2 a-d.</li> <li>null_sim_1.csv - null_sim_10.csv: the 10 null simulated datasets. Used to quantitatively compare CRAWDAD, Squidpy’s co-occurrence implementation, and Ripley’s K Cross.</li> </ul> <h2>HuBMAP Datasets</h2> <ul> <li>pkhl.csv: annotated cell types and positions of sample HBM389.PKHL.936 from donor HBM966.VNKN.965. Used in Figure 5 a-h, Supplementary Figure 5 a, Supplementary Figure 7 a-c, and Supplementary Figure 8 c. doi:10.35079/HBM389.PKHL.936</li> <li>xxcd.csv: annotated cell types and positions of sample HBM772.XXCD.697 from donor HBM966.VNKN.965. Used in Figure 5 d-h, Supplementary Figure 5 a-c, and Supplementary Figure 7 a-c. doi:10.35079/HBM772.XXCD.697</li> <li>fsld.csv: annotated cell types and positions of sample HBM342.FSLD.938 from donor HBM245.ZWNT.288. Used in Figure 5 e-f, h, Supplementary Figure 5 a-c, Supplementary Figure 6 a-b, and Supplementary Figure 7 a-c. doi:10.35079/HBM342.FSLD.938</li> <li>pbvn.csv: annotated cell types and positions of sample HBM825.PBVN.284 from donor HBM245.ZWNT.288. Used in Figure 5 e-f, h, Supplementary Figure 5 a-c, Supplementary Figure 6 a-b, and Supplementary Figure 7 a-c. doi:10.35079/HBM825.PBVN.284</li> <li>ksfb.csv: annotated cell types and positions of sample HBM556.KSFB.592 from donor HBM298.KGNJ.374. Used in Figure 5 e-f, h, Supplementary Figure 5 a-c, Supplementary Figure 6 a-b, and Supplementary Figure 7 a-c. doi:10.35079/HBM556.KSFB.592</li> <li>ngpl.csv: annotated cell types and positions of sample HBM568.NGPL.345 from donor HBM298.KGNJ.374. Used in Figure 5 e-f, h, Supplementary Figure 5 a-c, Supplementary Figure 6 a-b, and Supplementary Figure 7 a-c. doi:10.35079/HBM568.NGPL.345</li> </ul> <h2>External Datasets</h2> <ul> <li>Mouse cerebellum: Used in Figure 2 a-e, Supplementary Figure 3 a-b, Supplementary Figure 4 a-d, and Supplementary Figure 8 a.</li> <li>Mouse embryo: Used in Figure 2 f-j, Supplementary Figure 3 c-d, Supplementary Figure 4 e-h, and Supplementary Figure 8 b.</li> <li>Human breast cancer: Used in Figure 3 a-c.</li> <li>Mouse brains: Used in Figure 4 a-e.</li> </ul>
Post-consumer flexible packaging characterization
<p>Dataset on post-consumer waste flexible packaging </p> <p>Analysis of the composition made with FTIR spectrometer Antaris II </p> <p>200 Samples characterized</p> <p>Waste coming for French Material Recovery Facilities (Yellow bins) </p> <p> </p>
Stellar Evolution Models from "Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST"
<p>These data consist of all runs from the Modules for Experiments in Stellar Astrophysics (MESA; Paxton et al. 2011, 2013, 2015, 2018, 2019) code, used to construct radius priors for modeling supernova precursor emission in<em> <a href="https://arxiv.org/abs/2408.13314">Finding the Fuse: Prospects for the Detection and Characterization of Hydrogen-Rich Core-Collapse 5 Supernova Precursor Emission with the LSST</a></em> (Gagliano+2024, submitted). </p> <p>The contents of the data files are detailed in the file <strong>ReadmeMESA.txt</strong>. Additional detail concerning the simulations can be found in Section 2.2 of the linked publication. </p>
Mars 2020 Perseverance SHERLOC WATSON camera pre-delivery characterization and calibration image data
<p>The data presented here include images acquired by the WATSON (Wide Angle Topographic Sensor for Operations and eNgineering) camera during pre-delivery characterization and calibration testing at Malin Space Science Systems (MSSS, San Diego, California, USA) in September and October 2019. They also include video documentation of the camera’s dust cover motion. WATSON is one of two imaging subsystems of the SHERLOC (Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals) instrument onboard NASA’s Mars 2020 Perseverance rover which landed in Jezero crater, Mars, in February 2021.</p> <p>These data accompany the instrument calibration and characterization report by Edgett et al. (2019) and the WATSON characteristics reported by Bhartia et al. (2021). The image data presented here are listed and described in the Appendix to Edgett et al. (2019), which is also available here with the data.</p> <p>References cited:</p> <p>Bhartia, R., L. W. Beegle, L. DeFlores, W. Abbey, J. Razzell Hollis, K. Uckert, B. Monacelli, K. S. Edgett, M. R. Kennedy, M. Sylvia, D. Aldrich, M. Anderson, S. A. Asher, Z. Bailey, K. Boyd, A. S. Burton, M. Caffrey, M. J. Calaway, R. Calvet, B. Cameron, M. A. Caplinger, B. L. Carrier, N. Chen, A. Chen, M. J. Clark, S. Clegg, P. G. Conrad, M. Cooper, K. N. Davis, B. Ehlmann, L. Facto, M. D. Fries, D. H. Garrison, D. Gasway, F. T. Ghaemi, T. G. Graff, K. P. Hand, C. Harris, J. D. Hein, N. Heinz, H. Herzog, E. Hochberg, A. Houck, W. F. Hug, E. H. Jensen, L. C. Kah, J. Kennedy, R. Krylo, J. Lam, M. Lindeman, J. McGlown, J. Michel, E. Miller, Z. Mills, M. E. Minitti, F. Mok, J. Moore, K. H. Nealson, A. Nelson, R. Newell, B. E. Nixon, D. A. Nordman, D. Nuding, S. Orellana, M. Pauken, G. Peterson, R. Pollock, H. Quinn, C. Quinto, M. A. Ravine, R. D. Reid, J. Riendeau, A. J. Ross, J. Sackos, J. A. Schaffner, M. Schwochert, M. O Shelton, R. Simon, C. L. Smith, P. Sobron, K. Steadman, A. Steele, D. Thiessen, V. D. Tran, T. Tsai, M. Tuite, E. Tung, R. Wehbe, R. Weinberg, R. H. Weiner, R. C. Wiens, K. Williford, C. Wollonciej, Y.-H. Wu, R. A. Yingst, J. Zan (2021) Perseverance’s Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) investigation, Space Science Reviews 217, 58. https://doi.org/10.1007/s11214-021-00812-z</p> <p>Edgett, K. S., M. A. Caplinger, M. A. Ravine (2019) Mars 2020 Perseverance SHERLOC WATSON Camera Pre-delivery Characterization and Calibration Report, Malin Space Science Systems, San Diego, California. https://doi.org/10.13140/RG.2.2.18447.00165</p>
Molecular characterization and genetic diversity of four undescribed novel oleaginous Mortierella alpina strains from Libya
<p>A large number of undiscovered fungal species still exist on earth, which can be useful for bioprospecting, particularly for single cell oil (SCO) production. <em>Mortierella</em> is one of the significant genera in this field and contains about hundred species. Moreover, <em>M. alpina </em>is the main single cell oil producer / arachidonic acid producer at commercial scale under this genus.</p>
HELIX: Data-driven characterization of Brazilian land snails
<p>The Subulinidae family of Brazilian land snails includes similar species with particular morphometrical characteristics. We surveyed the metro area of the Juiz de Fora/MG city and collected snails from a representative private property with centered at 21º42'31''S, 43º21'26'', alt. 795m, with red-yellow oxisol, 8.5 pH, and Cwa climate. We performed monthly collections in a ecosystem with <em>Pennisetum purpureum</em>, <em>Brachiaria mutica</em>, <em>Paspalum notatum</em>, <em>Bidens pilosa</em>, <em>Leucena leucocephala</em>, and <em>Ricinus communis</em> plants near a river flow in the 2008/Sep - 2009/Aug timespan. There, we defined an equally spaced transect of 200m with ten collection points and gathered 50 x 50 cm, 500 g litter-falls. Samples were sieved by 2.0 mm meshs, and living specimens were cleaned and fixed in a Railliet-Henry liquid, their shells removed, dried, and separated. Finally, we label the species and create the Helix dataset. We measured each shell <em>Height</em>, <em>Diameter</em>, <em>Spire height</em>, and <em>Aperture width</em> and <em>height</em> with a pachymeter. The dataset includes 518 instances labeled as <em><strong>Beckianum beckianum</strong></em> (28.8%), <em><strong>Dysopeas muibum</strong></em> (21.2%), <em><strong>Allopeas gracilis</strong></em> (9.7%), <em><strong>Leptinaria unilamellata </strong></em>(12%), and <em><strong>Subulina octona</strong></em> (28.3%). </p>
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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.