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5,145 results for “CO₂”
X-ray absorption data and microscopic images of "Atomically dispersed iron(3+) sites catalyze efficient CO2 electroreduction to CO"
<p>XANES and EXAFS data (Figure 1F-H, Figure 3A-B, Figure S2F-H, Figure S3H-I, Figure S10A-B, Figure S11A-B,E-F, Figure S12A, Figure S14D-E)</p> <p>Microscopic images (Figure 1A-D, Figure S2B,D, Figure S4A-B,D-E, Figure S9A-C,E Figure S13A-D)</p> <p>of the research paper 'Atomically dispersed iron(3+) sites catalyze efficient CO2 electroreduction to CO'.</p>
Sentiment analysis of tech media articles using VADER package and co-occurrence analysis (01.2016-04.2019)
<p>Sentiment analysis of tech media articles using VADER package and co-occurrence analysis</p> <p><strong>Sources with weights:</strong></p> <ul> <li>Euractiv 5%</li> <li>The Conversation 5%</li> <li>Politico Europe 5 %</li> <li>IEEE Spectrum 5 %</li> <li>Techforge 5%</li> <li>Fastcompany 5%</li> <li>The Guardian (Tech) 12%</li> <li>Arstechnica 5%</li> <li>Reuters 5%</li> <li>Gizmodo 9%</li> <li>ZDNet 9%</li> <li>The Register 12%</li> <li>The Verge 9%</li> <li>TechCrunch 9%</li> </ul> <p><strong>Methodology</strong></p> <p>The sentiment analysis has been prepared using VADER*, an open-source lexicon and rule-based sentiment analysis tool. VADER is specifically designed for social media analysis, but can be also applied for other text sources. The sentiment lexicon was compiled using various sources (other sentiment data sets, Twitter etc.) and was validated by human input. The advantage of VADER is that the rule-based engine includes word-order sensitive relations and degree modifiers.</p> <p>As VADER is more robust in the case of shorter social media texts, the analysed articles have been divided into paragraphs. The analysis have been carried out for the social issues presented in the co-occurrence exercise.</p> <p>The process included the following main steps:</p> <ul> <li>The 100 most frequently co-occurring terms are identified for every social issue (using the co-occurrence methodology)</li> <li>The articles containing the given social issue and co-occurring term are identified</li> <li>The identified articles are divided into paragraphs</li> <li>Social issue and co-occurring words are removed from the paragraph</li> <li>The VADER sentiment analysis is carried out for every identified and modified paragraph</li> <li>The average for the given word pair is calculated for the final result</li> </ul> <p>Therefore, the procedure has been repeated for 100 words for all identified social issues.</p> <p>The sentiment analysis resulted in a compound score for every paragraph. The score is calculated from the sum of the valence scores of each word in the paragraph, and normalised between the values -1 (most extreme negative) and +1 (most extreme positive). Finally, the average is calculated from the paragraph results. Removal of terms is meant to exclude sentiment of the co-occurring word itself, because the word may be misleading, e.g. when some technologies or companies attempt to solve a negative issue. The neighbourhood's scores would be positive, but the negative term would bring the paragraph's score down.</p> <p>The presented tables include the most extreme co-occurring terms for the analysed social issue. The examples are chosen from the list of words with 30 most positive and 30 most negative sentiment. The presented graphs show the evolution of sentiments for social issues. The analysed paragraphs are selected the following way:</p> <ul> <li>The articles containing the given social issue are identified</li> <li>The paragraphs containing the social issue are selected for sentiment analysis</li> </ul> <p>*Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.</p>
Dataset - Anaerobic co-digestion of waste yeast biomass from citric acid production and waste frying fat
<p>Excel document that contains the data of the journal article “Moeller et al. (2018) Anaerobic co-digestion of waste yeast biomass from citric acid production and waste frying fat”. The dataset includes all values obtained during the experimental period and it complements the corresponding article.</p>
Dataset - Biogas production from concentrated yeast biomass by anaerobic (co)-digestion
<p>Excel document that contains the data of the anaerobic digestion of concentrated yeast biomass as mono-substrate under mesophilic and thermophilic conditions. The dataset includes all values obtained during the experimental period from 11/2018 – 08/2019. The data were obtained as measurement data of the experimental work on biogas production. These data form the basis for the calculation of yields and productivities and for evaluating the process stability.</p>
Recording of WWV 5 MHZ from Longmont, CO
<p>Event: WWV Centennial Festival of Frequency Measurements</p> <p>UTC Date: 20190801</p> <p>Beacon frequency: 5.000 000</p> <p>Station Name: K0ANS</p> <p>Latitude: 40.16290 N</p> <p>Long: 105.11797 W</p> <p>Grid: DN70kd</p> <p>City: Longmont, CO</p> <p>Difficulties had: My equipment has a observed frequency error of about 1 ppm when warmed up.</p> <p>Equipment: Yaesu FT-817ND with TCXO; warm-up started at about 23:00</p> <p>SW: fldigi ver 4.1.08</p> <p>Soapbox: I'm happy to participate.</p> <p>This close to WWV, I expect to receive either ground wave or NVIS. </p> <p> </p>
Fig. 1 in Devonian pearls and ammonoid-endoparasite co-evolution
Fig. 1. Terminology and measurements. For more information on the specimens see Figs. 2 and 5.
Fig. 1 in Co-infection of Echinococcus equinus and Echinococcus canadensis (G6/7) in a gray wolf in Turkey: First report and genetic variability of the isolates
Fig. 1. Stereomicroscopic view of adult parasites obtained from gray wolf's intestine.
BIR-MicroED: TEM image series revealing bend contour motion in static microcrystals (biotin, Zn(II)-methionine, Co(II)-porphyrin, AVAAGA) and diffraction patterns acquired from the same crystals at 200 kV
<p>This deposition contains a series zip files each containing TEM image series and electron diffraction images in .mrc file format. Each folder collects data acquired from crystals of a particular compound under the same conditions (electron energy, temperature). Zip files are named according to the format: <em>"CompoundName</em>_bendcontour_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>.zip"</p> <p>Data is further divided into sub-directories according to the particular crystal studied (crystal1, crystal2, crystal3), each containing a TEM image series (name format: "<em>CompoundName</em>_static_imageseries_<em>AcceleratingVoltage</em>_<em>Temperature</em>_crystal#.mrc") and 10 diffraction snapshots (2 frames each, each convering 1 second of electron beam exposure) acquired at equally spaced time intervals throughout the image series. These are named according to the format:</p> <p>"CompoundName_bendcontour_crystal#_diffraction_snap#.mrc"</p>
Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene co-expression networks
<p>Data and Inferred Networks accompanying the manuscript entitled - “Aggregation of recount3 RNA-seq data improves the inference of consensus and context-specific gene co-expression networks” </p> <p>Authors: Prashanthi Ravichandran, Princy Parsana, Rebecca Keener, Kaspar Hansen, Alexis Battle </p> <p>Affiliations: Johns Hopkins University School of Medicine, Johns Hopkins University Department of Computer Science, Johns Hopkins University Bloomberg School of Public Health</p> <p>Description: </p> <p>This folder includes data produced in the analysis contained in the manuscript and inferred consensus and context-specific networks from graphical lasso and WGCNA with varying numbers of edges. Contents include:</p> <ul> <li> <p>all_metadata.rds: File including meta-data columns of study accession ID, sample ID, assigned tissue category, cancer status and disease status obtained through manual curation for the 95,484 RNA-seq samples used in the study. </p> </li> <li> <p>all_counts.rds: log2 transformed RPKM normalized read counts for 5999 genes and 95,484 RNA-seq samples which was utilized for dimensionality reduction and data exploration </p> </li> <li> <p>precision_matrices.zip: Zipped folder including networks inferred by graphical lasso for different experiments presented in the paper using weighted covariance aggregation following PC correction.</p> </li> <ul> <li> <p>The networks can be found as follows. First, select the folder corresponding to the network of interest - for example, Blood, this will then include two or more folders which indicate the data aggregation utilized, select the folder corresponding appropriate level of data aggregation - either all samples/ GTEx for blood-specific networks, this includes precision matrices inferred across a range of penalization parameters. To view the precision matrix inferred for a particular value of the penalization parameter X, select the file labeled lambda_X.rds</p> </li> <li> <p>For select networks, we have included the computed centrality measures which can be accessed at centrality_X.rds for a particular value of the penalization parameter X. </p> </li> <li> <p>We have also included .rds files that list the hub genes from the consensus networks inferred from non-cancerous samples at “normal_hubs.rds”, and the consensus networks inferred from cancerous samples at “cancer_hubs.rds”</p> </li> <li> <p>The file “context_specific_selected_networks.csv” includes the networks that were selected for downstream biological interpretation based on the scale-free criterion which is also summarized in the Supplementary Tables. </p> </li> </ul> <li> <p>WGCNA.zip: A zipped folder containing gene modules inferred from WGCNA for sequentially aggregated GTEx, SRA, and blood studies. Select the data aggregated, and the number of studies based on folder names. For example, blood networks inferred from 20 studies can be accessed at blood/consensus/net_20. The individual networks correspond to distinct cut heights, and include information on the cut height used, the genes that the network was inferred over merged module labels, and merged module colors. </p> </li> </ul>
Dataset of "Gender analysis and co-authorship networks in the scientific production of oncology in Spain (2011–2021)"
Open the record for dataset details and reuse information.
Palladium-Catalyzed CO Oxidation
<p>Galaxy RO Crate object containing the workflow and data with the reproduction of the results published in: C. Stewart, E. K. Gibson, K. Morgan, G. Cibin, A. J. Dent, C. Hardacre, E. V. Kondratenko, V. A. Kondratenko, C. McManus, S. M. Rogers, C. E. Stere, S. Chansai, Y. -C. Wang, S. J. Haigh, P. P. Wells, A. Goguet (2018). Unraveling the H2Promotional Effect on Palladium-Catalyzed CO Oxidation Using a Combination of Temporally and Spatially Resolved Investigations DOI: 10.1021/acscatal.8b01509.</p> <div> <p>This RO is published as part of the research data submitted for the paper <strong>Facilitating Reproducibility in Catalysis Research with Managed Workflows and RO-Crates: A Galaxy Case Study</strong>, ChemCatChem, DOI: 10.1002/cctc.202401676.</p> </div>
Microscopic mechanism of the L1_2–D0_19 phase transformation in a Co-base single crystal superalloy
<p>This record contains datasets related to the publication:</p> <p>N. Karpstein et al., Microscopic mechanism of the L1<sub>2</sub>-D0<sub>19</sub> phase transformation in a Co-base single crystal superalloy, Acta Materialia (2024), <a href="https://doi.org/10.1016/j.actamat.2024.120416" target="_blank" rel="noopener">doi:10.1016/j.actamat.2024.120416</a>.</p> <p>A readme file containing descriptions of datatypes can be found in the main folder.</p> <p> </p> <p>Abstract:</p> <p>In γ′-strengthened superalloys based on the Co-Al-W system, the stability of the γ′ phase is often limited, as it is found to transform into other phases such as B2 and D0<sub>19</sub> after long-term annealing. To explore the details behind the annealing-induced transformation from the metastable L1<sub>2</sub>-γ′ phase to the thermodynamically stable D0<sub>19</sub>-χ phase in the single-crystalline Co-base superalloy ERBOCo-VF60 (Co<sub>79.8</sub>Al<sub>8.9</sub>W<sub>9.0</sub>Ta<sub>2.3</sub> in at.%), scanning transmission electron microscopy and atom probe tomography are employed. Due to the structural similarity between the L1<sub>2</sub> and D0<sub>19</sub> structures, coherent plate-shaped χ precipitates are formed in the γ/γ′ microstructure parallel to {111} planes through a shear-based transformation mechanism. While the χ phase precipitates slowly during isothermal aging, its formation can be significantly accelerated locally by coating the superalloy with a Cr-rich layer, which indirectly stabilizes the χ phase as revealed by thermodynamic calculations. This procedure allowed us to obtain an intermediate (incomplete) state of χ-phase formation in terms of both crystal structure and composition. By characterizing the partial dislocations at the tip of growing χ precipitates, the microscopic details of the shear-based cubic-to-hexagonal transformation from L1<sub>2</sub> to D0<sub>19</sub> are uncovered. The compositional aspect of the transformation involves a significant diffusion-mediated enrichment of W in the χ phase, accompanied by a simultaneous W depletion in the γ′ phase, leading to its transformation to the γ phase.</p>
Accessing Homo- and Heteroleptic α-Diimin Complexes (M = Fe, Co)
<p>The follwoing repository contains the cartesian coordinates of the calculated structures and the energies obtained by DFT-calculations. Please cite the original source/paper.</p>
Dataset for publication: "Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu"
<p>Dataset for the article: B.V. Padlyak, I.I. Kindrat, V.T. Adamiv, A. Drzewiecki, B. Cieniek, I. Stefaniuk, Structural and spectroscopic studies of lithium tetraborate glass co-doped with Sm and Cu, Phys. Chem. Chem. Phys. 26 (2024) 22006–22022, https://doi.org/10.1039/d4cp01633e.</p>
3D ED dataset of co-crystal of GRGDS peptide with trifluoroacetic acid (TFA)
<p>EPU-D electron diffraction dataset of the GRGDS TFA co-crystal. The original diffraction data is in MRC format, with all metadata stored in the PETS2 pts2 file. JANA files for absolute structure determination and dynamical refinement are also included.</p>
CO emission line spectra of the detected IRAM 30m CO-CAVITY galaxies.
<p>Figures show the observed spectra of the CO(1-0) and CO(2-1) emission lines of the CO-CAVITY galaxies.</p>
UV-radiated dissolved Co and Cu (dCo and dCu) along 30 deg E transect: GEOTRACES GIPr07 cruise
<p>The data describes the depth profiles of seawater concentration of dCo and dCu (0.2 µm filtered) along the 30 deg E transect in the Indian sector of Southern Ocean. </p>
Minimal dataset for study, Spatiotemporal patterns of individual and multiple simultaneous severe weather events co-occurring with power outages in the United States, 2018-2020
<p>These datasets are the minimal datasets for the study, Spatiotemporal patterns of individual and multiple simultaneous severe weather events co-occurring with power outages in the United States, 2018-2020.</p> <p>Study DOI: https://doi.org/10.21203/rs.3.rs-4752336/v1</p>
Data from: Density-dependent disease, life history tradeoffs, and the effect of leaf pathogens on a suite of co-occurring close relatives
1. Plant pathogens reduce the performance of their hosts and therefore may contribute to ecological mechanisms of coexistence. In Chesson's framework, pathogens contribute to stabilizing mechanisms when they intensify negative intraspecific interactions, such as density-dependent disease. Additionally, pathogens contribute to equalizing mechanisms when they reduce differences in performance among species. Life history tradeoffs predict higher susceptibility to pathogens in rapidly growing species, which could equalize performance among fast- and slow-growing species in the presence of pathogens. 2. In a coastal prairie in California, we studied the impact of leaf diseases on the performance of seventeen coexisting species of Trifolium and Medicago ("clovers"). We transplanted clovers in randomized arrays into the natural prairie community in three years of common garden experiments. We quantified infection rates by isolating fungi from leaves, and we measured disease severity as percent leaf area damaged. In a fungicide experiment, we measured the impact of infection on biomass and survival. We assessed whether disease on transplants was positively related to natural abundance of that species in the surrounding community, which we monitored over 5 years. We assessed life history tradeoffs by testing whether more rapidly growing species were more susceptible to pathogens. 3. Rank abundance of clover species was stable over five years despite marked environmental fluctuations. Across hosts, fungal infection was not linearly related to density, although transplants of species that were locally absent showed lower and more variable infection. Disease severity was greater for more abundant species in only one of three years, and response to fungicide was not stronger in more abundant species. Faster-growing species experienced greater fungal infection. Consistent with predictions of the leaf economic spectrum, the impact of infection on faster-growing species was less negative than for slower-growing species. 4. Our results suggest that life history tradeoffs in plant-pathogen interactions may contribute to equalizing mechanisms among species in this guild, but that the combined effects of greater infection with greater tolerance may limit rather than promote coexistence. We also found modest evidence that density-dependent disease may contribute to stabilizing mechanisms. Lack of host specificity, rapid evolution of host use, and temporal variation in climatic conditions may all influence the role that pathogens play in coexistence of these closely related plants.
A visualization of co-authorship network of mathematicians with an Erdős number of at most 2
<p>Co-authorship network of mathematicians with an Erdős number of at most 2</p> <p>Based on the data available at: https://oakland.edu/enp/thedata/erdos1.</p> <p>As can be seen, Erdős has collaborated directly or through an intermediary with different groups of scientists.<br> Researchers in the field of graph and computer science (gold), specialists in number theory (pink), mathematicians in the field of set theory (blue), researchers in the field of computer engineering (green) and the isolated group of Peter Salamon and his colleagues are the main groups of these researchers.<br> The names of researchers with more than 190 colleagues in the network (the first 10% of researchers) are written in the figure.</p> <p>See https://sites.google.com/oakland.edu/grossman/home/the-erdoes-number-project/the-erdoes-number-project-data-files.</p> <p>This artifact is a part of https://math-sci.ui.ac.ir/article_25684.html.</p>
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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.