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125 results for “Ei”
S70 | EISUSGCEIMS | Environmental Institute GC-EI-MS suspect list
<p>This is the collection associated with list S70 EISUSGCEIMS Environmental Institute GC-EI-MS suspect list on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>GC-EI-MS suspect list of Environmental Institute. Provided by Peter Oswald, Nikiforos Alygizakis, Martina Oswaldova, Jaroslav Slobodnik. Dataset DOI: <a href="https://doi.org/10.5281/zenodo.3894827">10.5281/zenodo.3894827</a>.</p>
S23 | EIUBASURF | Surfactant Suspect List from EI and UBA
<p>This is the collection associated with list S23 EIUBASURF on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S23</p> <p>EIUBASURF</p> <p><strong>Surfactant Suspect List from EI and UBA</strong></p> <p>Surfactant List <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/SurfactantSuspects_EI_UBA_15032018_wDTXSIDs.xlsx">XLSX</a> (19/06/2018)<br> Surfactant List <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/SurfactantSuspects_EI_UBA_15032018_wDTXSIDs.csv">CSV</a> (19/06/2018)<br> CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/eiubasurf">EIUBASURF List</a> </p> <p>EI UBA Surfactant <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/190618Update/SurfactantSuspects_EI_UBA_15032018_InChIKeys.txt">InChIKeys</a> (19/06/2018)</p> <p>A compiled list of eco-labeled surfactants from Environmental Institute (EI, SK) and the German Federal Environmental Agency (UBA, DE) assigning chemical structures to UVCB chemicals based on names and prior knowledge. Provided by Nikiforos Alygizakis, EI.</p>
EI Single-Cell RNA-Seq Workshop 2020
<p>Datasets to be used for the "Single-Cell RNA-Seq Workshop 2020" at the Earlham Institute, Norwich, UK.</p>
Chinese Calligraphy Reproduction Dataset with Writes' Trait EI
<p>This is a dataset of Chinese calligraphy reproductions, with 605 reference characters and 48,826 reproduced characters. The excel file contains the correspondence between reference characters and reproducedcharacters. In addition, it contains information about the writer's emotional intelligence. The dataset can be used to predict the writer's trait emotional intelligence from calligraphy reproduction.</p>
RECETOX Exposome HR-[EI+]-MS library
<p>The RECETOX Mass Spectrum Reference Libraries is a collection of MS spectra collected from authentic compounds. Each library comprises the spectra in MSP format and an accompanying SDF database of compounds. The collection is shared under terms & conditions of <a href="https://creativecommons.org/licenses/by-nc/4.0/">CC-BY-NC</a>.</p> <p>The RECETOX Exposome HR-[EI+]-MS library is a collection of mostly anthropogenic compounds. Spectra were acquired at 70 eV on Thermo Fisher Q Exactive™ GC Orbitrap™ GC-MS/MS at 60000 resolving power.</p>
RECETOX Metabolome HR-[EI+]-MS library
<p>The RECETOX Mass Spectrum Reference Libraries is a collection of MS spectra collected from authentic compounds. Each library comprises the spectra in MSP format and an accompanying SDF database of compounds. The collection is shared under terms & conditions of <a href="https://creativecommons.org/licenses/by-nc/4.0/">CC-BY-NC</a>.<br> <br> The RECETOX Metabolome HR-[EI+]-MS library is a collection of mostly endogoenous compounds from MetaSci Human Metabolite Library. Analytes underwent methoximation/silylation prior to acquisition. Spectra were acquired at 70 eV on Thermo Fisher Q Exactive™ GC Orbitrap™ GC-MS/MS at 60000 resolving power.</p>
LTER-Italy EBVs and EI indicators inventory
<p>The spreadsheet represents the inventory of Essential Biodiversity Variables (EBVs) and Ecosystem Integrity (EI) indicators monitored in Long Term Ecological Research (LTER) sites of LTER-Italy network.</p>
EI STFC Power of Light animation - introducing Big Questions and Diamond Light Source
<p>The ‘Power of Light’ project brings together research scientists, higher institution educators and research fellows, teachers, and STEM ambassadors to co-create engaging and accessible resources. The Power of Light project creates opportunities for classrooms and community settings to investigate examples of scientists’ current innovative research that is taking place in UK’s national synchrotron science facility at Diamond Light Source. </p> <p>This co-created animation identifies examples of Big Questions, introduces the synchrotron, and the value of exploring very small elements in our world to inform our thikning about Big Questions. During pilot sessions in both classroom and community settings, the animation has been successfully engaging curious minds and introducing areas of scientific research that can be explored further through the Power of Light 'zines'. This resource encourages a dialogue about the value of working in multidisciplinary ways to build and use knowledge in epistemically insightful ways.</p> <p>The particle accelerator at Diamond enables scientists to investigate the complexity of relationships in the structures of ‘things’ by investigating how atoms behave. The scientists we have been working with explain that they enter an area of research with a defined question that scientific methods and the facilities at Diamond can help them investigate. During their scientific research into a precise question further, and often unexpected, lines of enquiry can be disclosed. The Power of Light project confirms that learning about science (and how building scientific knowledge ‘works’) takes us on a journey of discovery about being human and the nature of the world around us.</p>
Database for accurate EI-MS spectra for volatile compounds identified in e-liquids for e-cigarettes
<p>Database of accurate EI-MS spectra, recorded using a GC-EI-TOF-MS instrument, for volatile and semi-volatile compounds tentatively identified in diluted e-liquids for e-smoking. Tentative identifications were based on normalized spectral matches above 75 (0-100 scale) with the low resolution NIST17 database, linear retention index differences between 50 units compared to literature values for semipolar (HP5-type) and Carbowax columns, and mass errors lower than 50 ppm for a minimum of two relevant ions in the spectra of each compound.</p> <p>The database can be used in combination with Library Editor software, included in MassHunter software. Experimental spectra were obtained after spectral deconvolution of GC-MS records for 1:100 diluted commercially available e-liquids</p>
Multimodal dataset: Protein Function Prediction using STRING data & COVID19 Mortality Model by EI
<p>The PFP.zip file contains 1. 5 well-formated GO terms dataset for EI, 2. STRING data 3. GO term annotation. The last two could be merged by the 'generate_data.py' script in https://github.com/GauravPandeyLab/ensemble_integration</p> <p>The covid19_model_built.zip contained the EI model built based on the COVID-19 Mortality dataset, the detail of usage are here:.</p>
GTN: Predicting EI+ mass spectra with QCxMS
<p>Dataset for the Galaxy Training for mass spectra prediction with QCxMS. The file contains the structures for Ethylene, Benzophenone, Enilconazole and Mirex.</p>
Database of retrosynthesis, SA-score and Ei values for AI-Design of ET MALDI matrices
Open the record for dataset details and reuse information.
Measurement-Based Spatially Explicit Methane Emission Inventory (EI-ME)
<p>Accurate and comprehensive assessment of methane emissions, a powerful climate warming pollutant, is a key first step in reducing these emissions, while supporting the ability to track progress toward such reductions over time. While national bottom-up source-level inventories are useful for understanding the sources of methane emissions, they are often unrepresentative across spatial scales, adn their reliance on generic emission factors produces underestimations when compared with measurement-based inventories.</p> <p>In this work, we compile and analyze previous peer-reviewed measurement-based data on facility-level methane emissions in the US oil and gas sector and use these data to develop statistically robust emissions models from which we estimate total methane emissions for the population of major US oil and gas facilities.</p> <p>This dataset (EI_ME_v1.0.gpkg) aggregates the results of this measurement-based methane emission inventory (EI-ME), which is focused on oil and gas methane emissions in the US onshore production regions. The emissions estimates are spatially resolved at 0.1 x 0.1 degree spatial scales.</p> <p>The data layers in the GeoPackage are:</p> <ul> <li><em>EI-ME_gridded_ch4_emissions:</em> estimated methane emissions, spatially resolved at 0.1x0.1 degree spatial grids</li> <li><em>EI-ME_US_oil_gas_basins:</em> major US oil and gas basin boundaries, based on <a href="https://www.eia.gov/maps/maps.php">EIA</a> basin boundary definitions.</li> <li><em>EI-ME_facility_ch4_measurements_data: </em>A compilation of previous peer-reviewed facility-level measurement-based data for oil and gas methane emissions in the US.</li> </ul> <p>We also provide a netcdf version ("EI_ME_2021_inventory_CONUS_point1_degrees_v1.nc") which includes estimated mean oil and gas methane emissions over the contiguous US (excludes Alaska) aggregated over a slightly offset spatial grid compared to the full domain in the above .gpkg.</p> <p>Complete details of the emissions model development and dataset creation can be found in the following manuscript:</p> <ul> <li><strong>How to cite: </strong>Omara, M., Himmelberger, A., MacKay, K., Williams, J. P., Benmergui, J., Sargent, M., Wofsy, S. C., and Gautam, R.: Constructing a measurement-based spatially explicit inventory of US oil and gas methane emissions (2021), Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, 2024.</li> </ul> <p>-----------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>UPDATE (10/10/2025):</p> <p>The spatially explicit measurement-based oil and gas methane emissions inventory (EI-ME) is developed by MethaneSAT, a wholly owned subsidiary of Environmental Defense Fund, to support comprehensive oil and gas methane assessment, methane source attribution, and mitigation. The inventory combines ground-based measurement-based data with statistically robust methane emissions modeling to provide representative estimates of total methane emissions for key facility categories in the contiguous US oil and gas supply chain, including well sites, natural-gas compressor stations, processing plants, crude-oil refineries, and pipelines. It is spatially resolved at 0.1x.0.1 degree spatial scales.</p> <p> Version 1 of the EI-ME inventory for the contiguous United States was published in 2024 and provided an estimate of the 2021 oil and gas methane emissions and uncertainties that are spatially resolved at 0.1x0.1 degree spatial scales.</p> <p> Here, we provide an update to the EI-ME inventory for the years 2023 and 2024. In this update, we follow the same methodology and use the same input emissions datasets as described in detail in Omara et al. (2024), https://doi.org/10.5194/essd-16-3973-2024. We incorporate the latest available oil and gas activity data for the years 2023 and 2024 based on data from Enverus Prism (<a href="http://www.eneverus.com/">www.eneverus.com</a>), supplemented with additional information from the Oil and Gas Infrastructure Mapping database (OGIM v2.7, <a href="https://doi.org/10.5281/zenodo.15103476">https://doi.org/10.5281/zenodo.15103476</a>) and global annual gas flaring data from VIIRS (Visible Infraed Imagin Radiometer Suite), available from the Earth Observation Group (<a href="https://eogdata.mines.edu/products/vnf/global_gas_flare.html">https://eogdata.mines.edu/products/vnf/global_gas_flare.html</a>).</p> <p>---</p> <p>Contact at Environmental Defense Fund: Mark Omara (momara@edf.org), Anthony Himmelberger (ahimmelberger@methanesat.org)</p> <p>---</p>
Low-frequency EIS intercept as a diagnostic tool for PEM fuel cells degradation
<p>Several diagnostic tests, such as polarization curves, electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV), were conducted periodically to monitor performance degradation during an accelerated stress test (AST) for catalyst degradation on a single proton exchange membrane (PEM) fuel cell, which involves voltage cycling. From the results of the EIS measurements taken during the AST at three different current densities, catalyst degradation is clearly shown. The lowfrequency intercept (Total R) increased most significantly. The simulation results with an 11-element impedance model show very good agreement with experimental data and consistency with the polarization change curves and CV. The obtained impedance at Total R is purely real, and it can be a useful and perhaps sufficient indicator for catalyst degradation and determination of the cell current state from just one parameter value, which is very promising for the future implementation in the PEM fuel cell control system</p>
FIGURES 12–14. Taenia talicei Dollfus, 1960. Metacestodes. 12. Polycephalic fimbriocercus. 13. Fimbriocercus. 14 in An endemic Taenia from South America: validation of T. tali c ei Dollfus, 1960 (Cestoda: Taeniidae) with characterization of metacestodes and adults
FIGURES 12–14. Taenia talicei Dollfus, 1960. Metacestodes. 12. Polycephalic fimbriocercus. 13. Fimbriocercus. 14. Cysticercus. Scale bar: 0.5 cm.
FIGURES 1–11. Taenia talicei Dollfus, 1960. 1–8. Adult form. 1 in An endemic Taenia from South America: validation of T. tali c ei Dollfus, 1960 (Cestoda: Taeniidae) with characterization of metacestodes and adults
FIGURES 1–11. Taenia talicei Dollfus, 1960. 1–8. Adult form. 1. Scolex (ventral view). 2. Scolex (apical view). 3–4. Rostellar hooks. 3. Large hooks. 4. Small hooks. 5. Mature segment. 6. Cirrus pouch and vagina. 7. Transverse section of mature segment. 8. Gravid proglottid. 9–11. Metacetodes. 9. Cysticercus. 10. Fimbriocercus. 11. Polycephalic forms. Scale bars in mm: 1, 0.5; 2, 0.3; 3–4, 0.05; 6, 0.25; 7, 1; 5 and 8–11, 2.
Supplementary material for the Hinode EIS calibration paper
<p>The files are associated with the paper describing the in-flight radiometric calibration of the<br>Hinode EIS instrument, see doi: 10.48550/arXiv.2308.06609<br> See the README file.</p> <p>The IDL save files contain a structure RETURN_STR with the results of the<br>fits of the single spectra, merged.</p> <p>The main array is return_str.total_counts which contains the<br>total counts in the lines for all the dates, in units of DN/s/1arc sec</p> <p>The array return_str.list_lambda has the expected wavelengths of the lines.</p> <p>The arrays in data_active_sfit_2023.save<br>return_str.eis_sw_ar_spectra and return_str.eis_lw_ar_spectra<br>contain the active region averaged spectra. </p> <p>The routine used to process Hinode EIS full spectral raster atlases<br>is process_atlas.pro</p> <p>The routine interpol_eis_ea.pro is to be used together with<br>the save file fit_eis_ea_2023-05-04_smooth.sav to obtain the<br>time and wavelength-dependent effective area.</p>
Supplementary material 1 from: Iorgu IȘ, Chobanov DP, Iorgu EI (2017) The unexpected finding of Parapholidoptera castaneoviridis in south-eastern Romania (Insecta, Orthoptera, Tettigoniidae). ZooKeys 643: 87-96. https://doi.org/10.3897/zookeys.643.10645
Occurrence records of Parapholidoptera castaneoviridis in the Balkan Peninsula : Explanation note: The occurrence records of Parapholidoptera castaneoviridis in the Balkan Peninsula, from literature and collected by the authors.
Supplementary material 1 from: Iorgu IS, Iorgu EI, Puskás G, Ivković S, Borisov S, Gavril VD, Chobanov DP (2016) Geographic distribution of Gryllotalpa stepposa in south-eastern Europe, with first records for Romania, Hungary and Serbia (Insecta, Orthoptera, Gryllotalpidae). ZooKeys 605: 73-82. https://doi.org/10.3897/zookeys.605.8804
Occurence records of the studied Gryllotalpa species : Explanation note: The occurence records of Gryllotalpa material preserved in the collections: MGAB, UBB, NMNHS, HMB, HNHM, ZZDBE, MNHM, CC.
Supplementary material 2 from: Fossen EI, Ekrem T, Nilsson AN, Bergsten J (2016) Species delimitation in northern European water scavenger beetles of the genus Hydrobius (Coleoptera, Hydrophilidae). ZooKeys 564: 71-120. https://doi.org/10.3897/zookeys.564.6558
Additional morphological characters : Explanation note: Word file containing a list and descriptions of additional morphological characters that were measured. Contains 11 external body and 8 male genital characters.
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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.