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5,145 results for “CO₂”
Tree-ring measurements from permanent study plot in old-growth hemlock-hardwood forest, Dukes RNA, Hiawatha NF, Marquette Co., MI
This package includes tree growth-ring widths for increment cores collected from a long-term 'macroplot' established in old-growth hemlock-northern hardwoods forest at the Dukes Research Natural Area/Dukes Experimental Forest in the Hiawatha National Forest in Marquette Co., MI. Tree demographic monitoring data for the entire ca. 3.0 ha macroplot, from 1992 to 2019, are available in the EDI package edi.1526.1. In 1993, 1994 and 1995, increment cores were taken for all 'core-able' trees greater than ~ 10 cm diameter for a subsection of the macroplot about 1 ha in area. Trees that were obviously badly rotten and hollow or steeply leaning were not cored. Cores are not cross-dated. See Methods for more details. This data-package may be cross-referenced to the demographic data in edi.1526.1 using stem numbers.
Macrophyte and microbial mat biomass co-variation along a hydrologic gradient and response to a removal experiment in temporary wetlands Everglades, FL, USA, February 2003 – November 2006
This data package encompasses hydrologic variables, soil depth, hydrologically-regulated macrophyte community types, macrophyte biomass and community structure, and microbial mat biomass that was collected in two observational surveys and one in-situ experimental manipulation in six temporary wetland regions located in the Everglades, FL, USA. The goal of this project was to examine the co-variation in macrophyte and microbial mat biomass along the hydrologic gradient present across wetland regions and to determine the type and strength of interactions occurring between the two communities, which was tested using a biomass (macrophyte or microbial mat) removal experiment. The census observational survey took place at 140 sites from 2003-04-09 to 2004-05-26, which were randomly distributed across the hydrologic gradient present across the six temporary wetland regions. The transect observational survey occurred along six transects and each was deliberately established along the present hydrologic gradient within each region; a total of 254 sites were sampled from 2003-02-19 to 2005-03-04. The experiment took place at three temporary wetland sites with contrasting hydroperiods (3 – 6 months), and four transects were established per site with 24 pairs of control and treatment plots per transect. The removal treatment occurred one year before data collection, and data collection occurred from 2004-06-20 to 2006-11-25. The package includes six datasets, one R code file, and two shape files associated with the R code. Data collection for all datasets is complete. FCE1274_Census_Survey includes hydrologically-regulated macrophyte community type classifications, macrophyte biomass, microbial mat ash-free dry mass, mean soil depth, water depth, mean annual hydroperiod, and vegetation-inferred hydroperiod; each site was sampled once during the survey period and a subset of sites were sampled each year. FCE1274_Transect_Survey includes macrophyte community type classifications
Dataset of "Activity-stability relationship in magnetron co-sputtered bimetallic catalysts for proton exchange membrane fuel cells"
<p>In the present study, magnetron sputtered PtxM100-x (M = Co, Cu, Y; x = 25, 50, 75 and 100) bimetallic alloys were investigated as PEMFC cathodes. Accurate composition control enabled a systematic study of the correlation between alloy composition, activity, and stability. The catalysts underwent thorough characterization, employing a diverse portfolio of characterization techniques such as scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy and cyclic voltammetry. The activity of all investigated alloys was tested directly in a fuel cell device, while stability was assessed through potentiodynamic cycling in a half-cell. <br>The activity-stability index, considering experimental results for both activity and stability, was calculated and compared for all investigated catalysts. All alloys exhibited a volcano-type trend in activity-stability index as a function of the concentration of alloying element with peaks observed at Pt50Co50, Pt50Cu50 and Pt75Y25 for respective alloys, surpassing that of monometallic platinum. Overall, Pt50Co50 emerged as a catalyst with the highest activity-stability ratio.</p>
Image data of co-localization of IgG and HEV ORF2 protein in a case of hepatitis E-associated kidney disease
<p><span>Image data for a co-localization study of IgG with HEV ORF2 protein in a </span><span>de novo immune complex-mediated glomerulonephritis (GN) case in</span><span> a kidney transplant recipient </span><span>with chronic hepatitis E (Leblond and Helmchen, et al. 2024).<span> </span>Immunofluorescence images are provided for 25 glomeruli at low magnification (20x, 0.227 micron/pixel) and for 16 glomeruli at high magnification (100x, 0.0454 micron/pixel). For each example glomeruli the green channel represents IgG antibody staining with FITC, and the magenta channel represent anti-HEV ORF2 staining using Alexa Fluor 546.</span></p> <p><span>Methods: </span></p> <p><span>Mouse monoclonal antibody clone 1E6 against the HEV ORF2 protein was incubated for 1h at a dilution of 1:125 followed by a mix of Alexa Fluor 546-conjugated goat anti-mouse antibody (Invitrogen BV, A11018) and FITC-conjugated Rabbit anti-Human IgG (Gamma chain, Diagnostic Biosystem, F008) for 1hat a dilution of 1:50. Following automated staining, the slides were hand -washed in distilled H<sub>2</sub>O. Tissue was covered with Vectashield® Antifade Mounting Medium with DAPI (VectorLaboratories, H-1200), covered with a coverslip and stored at 4°C until evaluation.</span></p> <p><span>Immunofluorescence images were acquired with an upright fluorescence microscope (AxioImager.Z2 controlled by ZEN Blue software; 89 North Photofluor LM-75 light source, and Axiocam 503 mono camera; Zeiss, Jena, Germany), equipped with the following objectives: 20x (NA 0.5, Plan-NEOFLUAR), 40x (NA 1.4 oil, Plan-APOCHROMAT), and 100x (NA 1.45 oil, Plan-APOCHROMAT) objectives. This setup provides an excellent spatial resolution (nominally about 200 nm lateral resolution in our study; pixel size was 45.4 nm for 100x objective). High resolution images were taken with the 100x objective using the ApoTome.2 module with deconvolution (grid 5 lp/mm; section thickness 0.7 µm). We used Vysis Abbott Chroma filter sets (Blue: excitation (ex) 335-383 nm, emission (em) 420-470; green: ex 481-507 nm; em 521-551 nm; red: ex 534-556 nm, em 574- 606 nm). Co-localization of IgG and HEV ORF2 staining was quantified using Fiji software (Schindelin et al., 2012) and the JACoP ImageJ plug-in. </span></p>
DisVis-based filtering of contacts from co-evolution data (or other sources)
<p>Dataset described in the manuscript: <em>Improving the Quality of Co-evolution Intermolecular Contact Prediction with DisVis</em>Siri Camee van Keulen, Alexandre M.J.J. Bonvin</p> <p>Details about the data set can be found at: https://github.com/haddocking/contact-filtering</p> <p>This archive contains in addition all the models generated with HADDOCK.</p>
Ecosystem metabolism and associated environmental data for a forested, meadow and reforested reach of White Clay Creek, Chester Co., Pennsylvania; 1971-1975 and 1997-2010
Ecosystem metabolism data for a 3rd-order Piedmont stream were collected during two periods: P1- April 1971 – Dec 1975, and P2- May 1997 – January 2010. Measures were made in a meadow and a forested reach during each period and in a reforested (formerly meadow) reach during the latter years of P2. During P1, measures were made by transferring streambed substrata to chambers in water jackets located on the streambank and measuring dissolved oxygen changes over diel periods. During P2, open system measures of dissolved O2 change were made for several days in warm and cold seasons, with reaeration determined from a propane injection experiment. Metabolism estimates were determined from diel curves of dissolved O2 change. Photosynthetically active radiation (PAR) and chlorophyll were measured concurrent with many measurements in P1 and all measures during P2, and temperature with all measures. Water chemistry parameters (NH4-N, NO3-N, PO4-P, SiO2, Cl, SO4, total alkalinity, pH) associated with each run are included in the data set, as are days since storm of various thresholds. Field procedures, analytical methods and data analyses are detailed in Bott, T.L. & J. D. Newbold, 2023. A multi-year analysis of factors affecting ecosystem metabolism in forested and meadow reaches of a Piedmont Stream. Hydrobiologia
Long-term (1935-2019) tree population data from remeasurements of a large network of permanent study plots in old-growth forest, Dukes Research Natural Area, Marquette Co., MI, USA
The Dukes Research Natural Area (Hiawatha National Forest, Marquette Co., MI) amounts to ca. 100 ha of minimally disturbed original forests, including a mix of mesic 'hemlock-northern hardwood' types and peaty wetlands dominated by several species of swamp conifers and black ash (Fraxinus nigra). The RNA hosts a regular grid of 250 0.2-acre (~0.08 ha) permanent monitoring (CFI) plots. This package includes tree censuses for subsets of CFI plots conducted in 1935, 1948, and 1974-1980, and repeated censuses with mapped stems from 1989 to 2019. This 84-year record constitutes one of the longest repeated-measurement, permanent-plot data-sets for old-growth temperate forest.
Data for: Techno-economic and environmental assessment of converting mixed prairie to renewable natural gas with co-product hydroxycinnamic acid, Iowa, USA, 2022-2023.
This dataset compiles model outputs, parameter sets, and documentation supporting a techno‑economic analysis (TEA) and life‑cycle assessment (LCA) of co‑digesting beef cattle manure with pretreated mixed prairie biomass to produce renewable natural gas (RNG), with hydroxycinnamic acids (HCA) and digestate‑derived biochar co‑products. It accompanies the study by Katherine Wild, Elmin Rahic, Lisa A Schulte Moore, and Mark Mba Wright "Techno-economic and environmental assessment of converting mixed prairie to renewable natural gas with co-product hydroxycinnamic acid," in Biofuels, Bioproducts, & Biorefining, 2024 (https://doi.org/10.1002/bbb.2710). The integrated simulation and assessment framework quantifies process performance, economics, and greenhouse‑gas intensity across five scenarios representing combinations of alkaline‑ethanol pretreatment for HCA extraction, liquid recirculation fractions, and biochar addition. This data collection includes: stream‑level mass flow/composition tables for each scenario; RNG, biochar, and HCA annual production summaries; literature‑based methane/biogas yield benchmarks; equipment‑level capital costs; TEA assumptions; emission‑factor inventories and displacement credits; and full sensitivity/uncertainty matrices for MFSP and GWP.
CO₂ and related biogeochemical data from permafrost rivers on the Qinghai-Tibet Plateau (2016–2018, 2023)
This dataset includes four years of direct measurements from 50 permafrost rivers in the Qinghai-Tibet Plateau’s major Asian headwaters (Yellow, Yangtze, Lancang, Nu, Derung, Yarlung Tsangpo, Marja Tsangpo, and Indus Rivers), collected during the ice-free seasons (April–October) of 2016–2018 and 2023. It includes CO₂ partial pressure (pCO₂) and emission rates, concentrations of DOC, DIC, and major dissolved ions, carbon (δ¹³C), sulfur (δ³⁴S), and oxygen (δ¹⁸O) isotopes, alongside site location and other physiochemical data. Given its scarcity and scientific significance, this dataset will greatly support updates to global river CO2 flux estimates.
Forage Resources in Warming and Removal Plots, Almont, CO, 2019
This is data collected to explore the impacts of warming and dominant species removal on the quantity and quality of plants for cattle foraging. The data were collected from the Colorado low elevation site (Almont) of the Warming and Removal in Mountains experiment which examines the direct and indirect impacts of climate change on plant and soil communities. Treatments include a control, warming (+1.5C), removal of the dominant species (Wyethia Amplexicalus), and both warming and dominant species removal. The dataset includes data that were collected in 2019 as well as historical data from the site. From 2019 we have in situ air temperature contained in and soil temperature data and an assessment of plant cover from every plot. We then have a compiled set of plant traits for each of the nine most common species including the leaf nitrogen, crude protein content, and forage quality class which are used for analysis on forage quality. The dataset also includes the annual plant cover data collected at peak season from 2013 to 2021 which was compared to daily temperature and precipitation data from the same date range collected by the National Oceanic and Atmospheric Administration. All reported figures and statistics published can be created from this data package.
A unified dataset of co-located sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia)
Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world's most ancient, biodiverse, and voluminous lake, has been experiencing localized sewage pollution from lakeside settlements. Increasing filamentous algal abundance suggests benthic communities are responding to this localized pollution. We surveyed 40-km of Lake Baikal's southwestern shoreline 19-23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics with co-located periphyton, macroinvertebrate, stable isotope, and fatty acid sampling. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset's 150+ variables. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage future reuse. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales.
Multi-year census of arthropod abundance on the plant Ligusticum porteri near Gothic, CO
The purpose of this study was to track year-to-year variation in aphid abundance on the host plant Ligusticum porteri (Apiaceae). We censused arthropod abundance on the flowering stalks of L. porteri weekly in June-August from 2012 to 2022. The censuses took place in ten L. porteri populations near the Rocky Mountain Biological Laboratory in Gothic, CO. While the same populations were used across years, we randomly selected ten flowering plants in each population in each year (N = 100 plants per year). Observations focused on colonization by the aphid Aphis asclepiadis, its mutualist ants, and natural enemies. When found, we counted other arthropods as well, identifying them to Family or Order in the field. We also counted the number of host plant flowering stalks and inflorescences (umbel). In 2016, we began tracking flowering phenology using a numerical score (0-8). To track senescence, we used a qualitative score (TB=turning brown and AB=all brown) for terminal and primary umbels.
Multi-year census of arthropod abundance on the plant Ligusticum porteri near Crested Butte, CO
The purpose of this study was to track year-to-year variation in aphid abundance on the host plant Ligusticum porteri (Apiaceae). We censused arthropod abundance on the flowering stalks of L. porteri weekly in June-August from 2017 to 2022. The censuses took place in ten L. porteri populations near Crested Butte, CO. The sites were by Brush Creek, Lake Irwin, and Washington Gulch. While the same populations were used across years, we randomly selected ten flowering plants in each population in each year (N = 100 plants per year). Observations focused on colonization by the aphid Aphis asclepiadis, its mutualist ants, and natural enemies. When found, we counted other arthropods as well, identifying them to Family or Order in the field. We also counted the number of host plant flowering stalks and inflorescences (umbel). We tracked flowering phenology using a numerical score (0-8). To track senescence, we used a qualitative score (TB=turning brown and AB=all brown) for terminal and primary umbels.
NOAA Monthly Mean Sea Level Summary Data for the Key West Water Level Station (NOAA/NOS Co-OPS ID 8724580), Florida, USA, January 1913 - ongoing
Monthly Mean Sea Level Summary Data for the Key West, Florida, Water Level Station (NOAA/NOS CO-OPS ID 8724580). Data is in meters relative to the STND-Key West Station Datum.
Co-dominant removal and N and C fertilization experiment for moist meadow tundra, 2002 - 2018.
In 2002 seven experimental sites were set up in areas of moist meadow alpine tundra on Niwot Ridge. At each site, ten 1 m^2 plots were established where there was roughly even cover by two dominant plant species, Geum rossii (forb) and Deschampsia cespitosa (grass). In a factorial design, plots were assigned treatments of 1) removal of G. rossii, D. cespitosa, or control (no plant removal), and 2) nutrient addition of nitrogen (N), carbon (C), or control (no addition). A tenth plot was assigned a treatment of random biomass removal and no nutrient addition. Plots were visited annually to implement removal and fertilization treatments, and to measure plant species composition. Plant productivity was measured every other year and nematode communities once via 18S rRNA metabarcoding, together with soils. Carbon addition plots were dropped from the experiment in 2016.
Model-based fMRI reveals co-existing specific and generalized concept representations
Open the record for dataset details and reuse information.
A long term hourly eddy covariance dataset of consistently processed CO2 and H2O Fluxes from the Tibetan Alpine Steppe at Nam Co (2005 - 2019)
<p>The data set contains nearly 15 years of eddy covariance data from an alpine steppe ecosystem on the central Tibetan Plateau. The data was processed following standardized quality control methods to allow for comparability between the different years of our record and with other data sets. To ensure meaningful estimates of ecosystem atmosphere exchange, careful application of the following correction procedures and analyses was necessary: (1) Due to the remote location, continuous maintenance of the eddy covariance (EC) system was not always possible, so that cleaning and calibration of the sensors was performed irregularly. Furthermore, the high proportion of bare soil and high wind speeds led to accumulation of dirt in the measurement path of the infrared gas analyzer (IRGA). The installation of the sensor in such a challenging environment resulted in a considerable drift in CO2 and H2O gas density measurements. If not accounted for, this concentration bias may distort the estimation of the carbon uptake. We applied a modified drift correction procedure following Fratini et al. (2014) which, instead of a linear interpolation between calibration dates, uses the CO2 concentration measurements from the Mt. Waliguan atmospheric observatory as reference time series. (2) We applied rigorous quality filtering of the calculated fluxes to retain only fluxes which represent actual physical processes. (3) During the long measurement period, there were several buildings constructed in the near vicinity of the EC system. We investigated the influence of these obstacles on the turbulent flow regime to identify fluxes with uncertain land cover contribution and exclude them from subsequent computations. (4) We calculated the de-facto standard correction for instrument surface heating during cold conditions (hereafter called sensor self heating correction) following Burba et al. (2008) and a revision of the original method following Frank and Massman (2020). (5) Subsequently, we applied the traditional and widely used gap filling procedure following Reichstein et al. (2005) to provide a more complete overview of the annual net ecosystem CO2 exchange. (6) We estimated the flux uncertainty by calculating the random flux error (RE) following Finkelstein and Sims (2001) and by using the standard deviation of the fluxes used for gap filling (NEE_fsd) as a measure for spatial and temporal variation.</p> <p>References:</p> <ol> <li>Burba, G. G., McDermitt, D. K., Grelle, A., Anderson, D., and XU, L. (2008). Addressing the influence of instrument surface heat exchange on the measurements of CO2 flux from open-path gas analyzers, Global Change Biology, 14, 1854-1876, <a href="https://doi.org/10.1111/j.1365-2486.2008.01606.x">https://doi.org/10.1111/j.1365-2486.2008.01606.x</a>.</li> <li>Finkelstein, P. L. and Sims, P. F. (2001). Sampling error in eddy correlation flux measurements, J. Geophys. Res. Atmos., 106, 3503–3509, doi:10.1029/2000JD900731.</li> <li>Frank, J. M. and Massman, W. J.: A new perspective on the open-path infrared gas analyzer self-heating correction, Agricultural and Forest Meteorology, 290, 107986, doi:10.1016/j.agrformet.2020.107986, 2020.</li> <li>Fratini, G., McDermitt, D. K., and Papale, D. (2004). Eddy-covariance flux errors due to biases in gas concentration measurements: origins, quantification and correction, Biogeosciences, 11, 1037-1051, <a href="https://doi.org/10.5194/bg-11-1037-2014">https://doi.org/10.5194/bg-11-1037-2014</a>.</li> <li>Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-m., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., and valentini, R. (20050. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biology, 11, 1424-1439, <a href="https://doi.org/10.1111/j.1365-2486.2005.001002.x">https://doi.org/10.1111/j.1365-2486.2005.001002.x</a>.</li> </ol>
Ferromagnetic resonance of Co thin films grown by atomic layer deposition on the Sb2Te3 topological insulator (data)
<p>This dataset contains the raw data files connected with the figures included in the paper "<em>Ferromagnetic resonance of Co thin films grown by atomic layer deposition on the Sb<sub>2</sub>Te<sub>3</sub> topological insulator</em>" by E. Longo et al., JMMM 209, 166885 (2020): <a href="https://linkinghub.elsevier.com/retrieve/pii/S0304885319336029">https://linkinghub.elsevier.com/retrieve/pii/S0304885319336029</a></p>
ChinaHighCO: Daily Seamless 1 km Ground-Level CO Dataset for China (2019–Present)
<p>ChinaHighCO is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.</p> <p>Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 1 km (i.e., D1K, M1K, and Y1K) ground-level CO dataset for China <strong>from 2019 to the present</strong>. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R<sup>2</sup>) of 0.80, a root-mean-square error (RMSE) of 0.29 mg m<sup>-3</sup>, and a mean absolute error (MAE) of 0.16 mg m<sup>-3</sup> on a daily basis.</p> <p>If you use the ChinaHighCO dataset in your scientific research, please cite the following reference (Wei et al., ACP, 2023):</p> <ul> <li> <p>Wei, J., Li, Z., Wang, J., Li, C., Gupta, P., and Cribb, M. <a href="https://weijing-rs.github.io/publications/Wei_et_al-ACP-2023.pdf">Ground-level gaseous pollutants (NO<sub>2</sub>, SO<sub>2</sub>, and CO) in China: daily seamless mapping and spatiotemporal variations</a>. <em>Atmospheric Chemistry and Physics</em>, 2023, 23, 1511–1532. https://doi.org/10.5194/acp-23-1511-2023</p> </li> </ul> <p><strong>Note that the ChinaHighCO<sub> </sub>dataset is also available for periods prior to 2019, but at a spatial resolution of 10 km:</strong></p> <p> all (including <strong>daily</strong>) data for the years <strong>2013–2018 </strong>are accessible at: <strong><a href="https://doi.org/10.5281/zenodo.4641530">https://doi.org/10.5281/zenodo.4641530</a></strong></p> <p><strong>More CHAP datasets for different air pollutants are available at: <a href="https://weijing-rs.github.io/product.html">https://weijing-rs.github.io/product.html</a></strong></p>
ChinaHighCO: Daily Seamless 10 km Ground-Level CO Dataset for China (2013–2018)
<p>ChinaHighCO is part of a series of long-term, seamless, high-resolution, and high-quality datasets of air pollutants for China (i.e., ChinaHighAirPollutants, CHAP). It is generated from big data sources (e.g., ground-based measurements, satellite remote sensing products, atmospheric reanalysis, and model simulations) using artificial intelligence, taking into account the spatiotemporal heterogeneity of air pollution.</p> <p>Here is the big data-derived seamless (spatial coverage = 100%) daily, monthly, and yearly 10 km (i.e., D10K, M10K, and Y10K) ground-level CO dataset for China <strong>from 2013 to 2018</strong>. This dataset exhibits high quality, with a cross-validation coefficient of determination (CV-R<sup>2</sup>) of 0.80, a root-mean-square error (RMSE) of 0.29 mg m<sup>-3</sup>, and a mean absolute error (MAE) of 0.16 mg m<sup>-3</sup> on a daily basis.</p> <p>If you use the ChinaHighCO dataset in your scientific research, please cite the following reference (Wei et al., ACP, 2023):</p> <ul> <li> <p>Wei, J., Li, Z., Wang, J., Li, C., Gupta, P., and Cribb, M. <a href="https://weijing-rs.github.io/publications/Wei_et_al-ACP-2023.pdf">Ground-level gaseous pollutants (NO<sub>2</sub>, SO<sub>2</sub>, and CO) in China: daily seamless mapping and spatiotemporal variations</a>. <em>Atmospheric Chemistry and Physics</em>, 2023, 23, 1511–1532. https://doi.org/10.5194/acp-23-1511-2023</p> </li> </ul> <p><strong>Note that the ChinaHighCO dataset was improved to a 1 km resolution after 2019:</strong></p> <p> all (including <strong>daily</strong>) data for the years after <strong>2019 </strong>are accessible at: <strong><a href="https://doi.org/10.5281/zenodo.10477022">https://doi.org/10.5281/zenodo.10477022</a></strong></p> <p><strong>More CHAP datasets for different air pollutants are available at: <a href="https://weijing-rs.github.io/product.html">https://weijing-rs.github.io/product.html</a></strong></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.