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861 results for “data comparison”
Data for Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing
<p>Data for<em> Survival probabilities of atmospheric particles: comparison based on theory, cluster population simulations, and observations in Beijing </em>(https://doi.org/10.5194/acp-2022-484)</p> <p>Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.</p>
Simulation Data & R scripts for: "Introducing recurrent events analyses to assess species interactions based on camera trap data: a comparison with time-to-first-event approaches"
<p><strong>Files descriptions:</strong></p> <p>All csv files refer to results from the different models (PAMM, AARs, Linear models, MRPPs) on each iteration of the simulation. One row being one iteration. <br>"results_perfect_detection.csv" refers to the results from the first simulation part with all the observations.<br>"results_imperfect_detection.csv" refers to the results from the first simulation part with randomly thinned observations to mimick imperfect detection.</p> <p>ID_run: identified of the iteration (N: number of sites, D_AB: duration of the effect of A on B, D_BA: duration of the effect of B on A, AB: effect of A on B, BA: effect of B on A, Se: seed number of the iteration).<br>PAMM30: p-value of the PAMM running on the 30-days survey.<br>PAMM7: p-value of the PAMM running on the 7-days survey.<br>AAR1: ratio value for the Avoidance-Attraction-Ratio calculating AB/BA.<br>AAR2: ratio value for the Avoidance-Attraction-Ratio calculating BAB/BB.<br>Harmsen_P: p-value from the linear model with interaction Species1*Species2 from Harmsen et al. (2009).<br>Niedballa_P: p-value from the linear model comparing AB to BA (Niedballa et al. 2021).<br>Karanth_permA: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species A (Karanth et al. 2017).<br>MurphyAB_permA: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>MurphyBA_permA: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>Karanth_permB: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species B (Karanth et al. 2017).<br>MurphyAB_permB: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br>MurphyBA_permB: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br> </p> <p>"results_int_dir_perf_det.csv" refers to the results from the second simulation part, with all the observations.<br>"results_int_dir_imperf_det.csv" refers to the results from the second simulation part, with randomly thinned observations to mimick imperfect detection.<br>ID_run: identified of the iteration (N: number of sites, D_AB: duration of the effect of A on B, D_BA: duration of the effect of B on A, AB: effect of A on B, BA: effect of B on A, Se: seed number of the iteration).<br>p_pamm7_AB: p-value of the PAMM running on the 7-days survey testing for the effect of A on B.<br>p_pamm7_AB: p-value of the PAMM running on the 7-days survey testing for the effect of B on A.<br>AAR1: ratio value for the Avoidance-Attraction-Ratio calculating AB/BA.<br>AAR2_BAB: ratio value for the Avoidance-Attraction-Ratio calculating BAB/BB.<br>AAR2_ABA: ratio value for the Avoidance-Attraction-Ratio calculating ABA/AA.<br>Harmsen_P: p-value from the linear model with interaction Species1*Species2 from Harmsen et al. (2009).<br>Niedballa_P: p-value from the linear model comparing AB to BA (Niedballa et al. 2021).<br>Karanth_permA: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species A (Karanth et al. 2017).<br>MurphyAB_permA: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>MurphyBA_permA: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species A (Murphy et al. 2021). <br>Karanth_permB: rank of the observed interval duration median (AB and BA undifferenciated) compared to the randomized median distribution, when permuting on species B (Karanth et al. 2017).<br>MurphyAB_permB: rank of the observed AB interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br>MurphyBA_permB: rank of the observed BA interval duration median compared to the randomized median distribution, when permuting on species B (Murphy et al. 2021). <br> </p> <p><strong>Scripts files description:</strong><br>1_Functions: R script containing the functions:<br> - MRPP from Karanth et al. (2017) adapted here for time efficiency.<br> - MRPP from Murphy et al. (2021) adapted here for time efficiency.<br> - Version of the ct_to_recurrent() function from the recurrent package adapted to process parallized on the simulation datasets.<br> - The simulation() function used to simulate two species observations with reciprocal effect on each other.<br>2_Simulations: R script containing the parameters definitions for all iterations (for the two parts of the simulations), the simulation paralellization and the random thinning mimicking imperfect detection.<br>3_Approaches comparison: R script containing the fit of the different models tested on the simulated data.<br>3_1_Real data comparison: R script containing the fit of the different models tested on the real data example from Murphy et al. 2021.<br>4_Graphs: R script containing the code for plotting results from the simulation part and appendices.<br>5_1_Appendix - Check for similarity between codes for Karanth et al 2017 method: R script containing Karanth et al. (2017) and Murphy et al. (2021) codes lines and the adapted version for time-efficiency matter and a comparison to verify similarity of results.<br>5_2_Appendix - Multi-response procedure permutation difference: R script containing R code to test for difference of the MRPPs approaches according to the species on which permutation are done.</p>
Supplementary data for: Comparison of transcriptomic profiles between HFPO-DA and prototypical PPARa, PPARg, and cytotoxic agents in mouse, rat, and pooled human hepatocytes
<p>Like many per- or polyfluorinated alkyl substances (PFAS), toxicity studies with HFPO-DA (ammonium,2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate), a short-chain PFAS used in the manufacture of some types of fluorinated polymers, indicate that the liver is the primary target of toxicity in rodents following oral exposure. Although the current weight of evidence supports the PPARa mode of action (MOA) for liver effects in HFPO-DA-exposed mice, alternate MOAs have also been hypothesized including PPARg or cytotoxicity. To further evaluate the MOA for HFPO-DA in rodent liver, transcriptomic analyses were conducted on samples from primary mouse, rat and pooled human hepatocytes treated for 12, 24 or 72 hours with various concentrations of HFPO-DA, or agonists of PPARa (GW7647), PPARg (rosiglitazone), or cytotoxic agents (i.e., acetaminophen or d-galactosamine). Concordance analyses of enriched pathways across chemicals within each species demonstrated greatest concordance between HFPO-DA and PPARa agonist GW7647-treated hepatocytes compared to the other chemicals evaluated. These findings were supported by benchmark concentration modeling and predicted upstream regulator results. In addition, transcriptomic analyses across species demonstrated a greater transcriptomic response in rodent hepatocytes treated with HFPO-DA or agonists of PPARa or PPARg, indicating rodent hepatocytes are more sensitive to HFPO-DA or PPARa/g agonist treatment. These results are consistent with previously published transcriptomic analyses and further support that liver effects in HFPO-DA-exposed rodents are mediated through rodent-specific PPARa signaling mechanisms as part of the MOA for PPARa activator-induced rodent hepatocarcinogenesis. Thus, effects observed in mouse liver are not appropriate endpoints for toxicity value development for HFPO-DA in human health risk assessment.</p>
Rock magnetic data from IODP Exp. 382 Sites U1537 and U1538 to support Reilly et al. "A geochemical mechanism for >10 m offsets of magnetic reversals inferred from the comparison of two Scotia Sea drill sites"
<p>Rock magnetic data from IODP Exp. 382 Sites U1537 and U1538 to support Reilly et al. "A geochemical mechanism for >10 m offsets of magnetic reversals inferred from the comparison of two Scotia Sea drill sites"</p><p>Excel Files:</p><ul><li>U1537_CubeSummary_Zenodo.xlsx : Summary of NRM, ARM, IRM, and magnetic susceptibility investigations on U1537 cube samples</li><li>U1538_CubeSummary_Zenodo.xlsx : Summary of NRM, ARM, IRM, and magnetic susceptibility investigations on U1538 cube samples</li></ul><p>Zip Files:</p><ul><li>FORC_Data.zip : First order reversal curve data files in MicroMag format for samples discussed in paper</li><li>DCD_Data.zip : DC Demagnetization curve data files for samples discussed in paper</li><li>Hysteresis_Data.zip : Hysteresis Loops for samples discussed in paper</li><li>MPMS_Data.zip : Data collected on Magnetics Property Measurement System 3, including Field Cooled/Zero Field Cooled Curves, Low Temperature Cycling of Room Temperature IRM, and AC Susceptibility</li></ul><p> </p><p>NRM = Natural Remanent Magnetization; ARM = Anhysteretic Remanent Magnetization; IRM = Isothermal Remanent Magnetization</p>
Stationary comparison data and analysis between a new low-cost meteorological device and the Technical University of Dresden Chair of Meteorology's backpack meteorological device
<p>This dataset provides stationary comparison data which was used to demontrate the suitability of a new low-cost and user-friendly meteorological device for the purpose of thermal comfort mapping. The new device was compared to an established high-end backpack-mounted device from the Dresden University of Technology (TUD) Chair of Meteorology, Germany. The main sensors for comparison were: the low-cost SHT 85 Sensirion sensor vs. the high-cost WXT520 for air temperature and relative humdity and the low-cost SR2AD pyranometer vs. the high-cost SKS 1110 pyranometer.</p>
Stationary comparison data and analysis between a new low-cost meteorological device and the MaRTy device
<p>This dataset provides stationary comparison data which was used to demontrate the suitability of a new low-cost and user-friendly meteorological device for the purpose of thermal comfort mapping. The new device was compared to the established high-end MaRTy device developed by Arizona State University's Sensable Heatscapes and Digital Environments (SHaDE) lab. The main sensors for comparison were: the low-cost SHT 85 Sensirion sensor vs. the high-cost HC2S3 Rotronic HygroClip2 for air temperature and humidity. However, the main purpose of the analysis was a comparison of the ability to predict Mean Radiant Temperature (MRT) as an essential component of thermal comfort. MRT for the low-cost device was calculated using the RayMan Pro software, while MRT for the MaRTy device is an output calculated directly by the device. </p>
Mobile comparison data and analysis between a new low-cost meteorological device and the Technical University of Dresden Chair of Meteorology's backpack meteorological device
<p>This dataset provides mobile comparison data from Tharandt and Dresden, Germany, which was used to demontrate the suitability of a new low-cost and user-friendly meteorological device for the purpose of thermal comfort mapping. The new device was compared to an established high-end backpack-mounted device from the Dresden University of Technology (TUD) Chair of Meteorology, Germany. The main sensors for comparison were: the low-cost SHT 85 Sensirion sensor vs. the high-cost WXT520 for air temperature and relative humdity and the low-cost SR2AD pyranometer vs. the high-cost SKS 1110 pyranometer. The ability of each device to predict the Universal Thermal Climate Index (UTCI), calculated using the software RayMan Pro, was also compared.</p>
FIGURE 5 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 5. SEM micrographs of selected plant macrofossils from Mary Sachs gravel at Duck Hawk Bluffs, southern Banks Island. (A) Microdiptera/Mneme type (Lythraceae), seed, cross-section with germination valve to top, sample MRA 7-18-91-3, GSC 141399; note the absence of obvious dorsal furrows as seen on specimen from the Ballast Brook Formation (Fyles et al., 1994). Germination valve contains approximately ten rows of pits; (B) Parthenocissus? (Vitaceae), half of seed, ventral face showing one ventral infold, sample MRA 7-1-88-2, GSC 141400; (C) Microdiptera/Mneme type (Lythraceae), two joined seeds, ventral view with apex up, sample MRA 7-18-91-3, GSC 141401; note that the specimen on the right contains a fold on the wing, undoubtedly due to packing of the seeds in the capsule. This indicates how one of the characters used to distinguish Microdiptera from Mneme, relative development of the 'wings' is likely due to considerable variation even in seeds from the same plant and supports Tiffneyʼs (1981) conclusion about the dubious validity of the many named species; (D) Orchidaceae?, seed, sample FG 91-13a, GSC 141402; (E) Nigrella sp. (Melastomaceae), seed, from the site 3 type section of the Ballast Brook Formation (see Fyles et al. 1994), GSC 141421.
FIGURE 9 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 9. SEM micrographs of selected plant fossils from Neogene deposits in the high terrace sections on Ellesmere Island, and Beaufort Formation, Meighen Island. (A) cf. Tubela (Betulaceae), seed, Riediger site, Ellesmere Island, Nunavut, sample FG 89-28a, GSC 141414; a specimen very similar to this one was dissected and found to contain an Alnus-type seed like those referred to A. tertiaria in Matthews, 1987; (B) Picea mariana/rubra type (Pinaceae), cross-section of needle showing resin canals (arrows), Beaver Peat, Ellesmere Island, Nunavut, sample FG- 88-51b, GSC 141415; (C) Thesium? (Santalaceae), seed, Prince Patrick Island, NWT, Green Bay beds, sample FG 87-10a/2, GSC 141416; (D) Calla sp. (Araceae), seed, Beaver Pond, Ellesmere Island, Nunavut, FG 88-8b, GSC 141417; (E) Unknown seed, Beaver Pond, Ellesmere Island, Nunavut, FG-88-8b, GSC 141418; (F) Comptonia sp. (Myricaceae), seed, Meighen Island, Nunavut, sample MRA 7-25-75-5, GSC 141419.
FIGURE 8 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 8. Selected leaf fossils from the Fyles Leaf Beds site (17), Ellesmere Island, Nunavut. Scale bar equals 10 mm. (A–V) Betula spp. (Betulaceae). Note the diversity of types ranging from some similar to those from the dwarf shrub species, B. nana (e.g., D, G, O, Q), contrasted with others (e.g., S, U, V) which are more typical of high shrub and tree species of Betula; (W) Skeletonized leaf of Salix, very similar to the type seen in S. reticulata (Salicaceae). (X) Fragment of Vaccinium sp. (Ericaceae) leaf showing peculiar circular perforations; (Y) Skeletonized leaf of Salix sp. (Salicaceae); (Z) Photograph of leaves in situ in the alternating sand and organic layers of Fyles Leaf Beds. (AA– II) Dryas cf. octopetala type (Rosaceae).
FIGURE 1 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 1. Distribution of sites and geographical features mentioned in the text. Siberian localities are from Baranova and Biske (1979). Shaded areas are shown in greater detail in Figures 2 and 4. Numbers refer to site codes used in Appendix 1 and throughout this paper.
FIGURE 7 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 7. SEM micrographs of selected plant macrofossils from Mary Sachs gravel at Duck Hawk Bluffs, southern Banks Island, NWT. (A) Saxifraga sp. (Saxifragaceae), seed, sample FG 91-13a, GSC 141407; (B) Hydrangea?, sample FG 91-13a, GSC 141408; (C) Morus sp. (Moraceae), seed, sample MRA 7-23-85-2, GSC 141409; (D) Physalis sp. (Solanaceae), seed, sample MRA 7-7-88-3, GSC 141412; note in magnified view of the seed the pits in the lumina which distinguish Physalis from Solanum (Mai and Walther, 1988); (E) Teucrium sp. (Lamiaceae), seed, sample MRA 7-18-91-3, GSC 141413.
FIGURE 3 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 3. SEM micrographs of Epipremnum from Banks Island. (A) Epipremnum seed, external view, Ballast Brook, "lower Beaufort Lignite", GSC 108847; (B) Epipremnum seed, internal view, Ballast Brook Formation, lower member, Sample 2, GSC 141420.
FIGURE 10 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 10. Correlation diagram. See text for details. Black circles and sites in bold face are independently dated. Note scale change in the Miocene part of the table. Double pointed arrows indicate possible age range of the site. Shaded column between certain sets indicates sites in stratigraphic superposition. Grey dotted line (10) indicates that although the flora appears mid-Miocene, the flora and surrounding sediment may have been redeposited much later. (1) Lava Camp mine, western Alaska (5.9 Ma); (2) Lost Chicken mine, east central Alaska (2.9 Ma); (3) Niguanak site, northern Alaska; (4) Cone Bluff, Porcupine River, east central Alaska; (5) Canyon Village section, Porcupine River, east central Alaska (6.4 Ma, late Miocene); (6) Upper Ramparts site, Porcupine River, east central Alaska (16 Ma); (7) Circle Gravels, east central Alaska (early Pliocene); (8a and 8b) Chʼijeeʼs Bluff, Unit 1 (8a) and Unit 2 (8b), northern Yukon; (9a and 9b) Bluefish Section, northern Yukon; (10) Mary Sachs gravel, southern Banks Island, NWT; (11a and 11b) Ballast Brook Formation (11a) and Beaufort Formation (11b) at Ballast Brook, northern Banks Island, NWT; (12a and 12b) Prince Patrick Island, NWT; typical Beaufort deposits from many sites on the island (12a) and Green Bay beds (12b); (13) Melville Island, NWT; Beaufort Formation; (14) Bathurst Island, Nunavut; Beaufort Formation; (15a and 15b) Meighen Island, Nunavut; deposits below (15a) and above (15b) the approximately 3 Ma marine unit within the Beaufort Formation; (16) Beaver Pond locality, Strathcona Fiord, Ellesmere Island, Nunavut (3.9 Ma); (17) Fyles Leaf beds site near the Beaver Pond locality at Strathcona Fiord, Ellesmere Island, NWT (3.8 Ma); (18a) Riediger Site, Ellesmere Island, NWT; (18b) Site within 2 km of Riediger Site, Ellesmere Island, Nunavut; (19a) Rochon Site, Vendom Fiord region, Ellesmere Island, Nunavut; (19b) Typical high terrace sediments near the Rochon site on Vendom Fiord, Ellesmere Island, Nunavut; (20) Isachsen Site near the head of Makinson Inlet, Ellesmere Island, Nunavut; (21) Capping gravels and sands at Geodetic Hills Eocene locality, Axel Heiberg Island, Nunavut; (22) West River site near Horton River upland, northern mainland, coast, NWT; (23) Plateau Cap gravels, Horton upland, northern mainland coast, NWT; (24) Remus Creek site, Fosheim Peninsula, Ellesmere Island, NWT; (25) South Bay site, Fosheim Peninsula, Ellesmere Island, Nunavut; (26) Fosheim Dome, Fosheim Peninsula, Ellesmere Island, Nunavut.
FIGURE 6 in Neogene and early Pleistocene flora from Alaska, USA and Arctic/Subarctic Canada: New data, intercontinental comparisons and correlations
FIGURE 6. SEM micrographs of selected plant macrofossils from the Neogene on the Canadian Arctic Archipelago. (A) Rubus sp. (Rosaceae), seed, Mary Sachs gravel, sample MRA 7-7-88-1, GSC 141422; (B) Ludwigia sp. (Onagraceae), seed, Mary Sachs gravel, sample FG 91-13a, GSC 141403; (C) Verbena sp. (Verbenaceae), seed, Prince Patrick Island, NWT, Beaufort Formation, GSC 141404; (D) Unknown seed; Beaver Pond, Ellesmere Island, Nunavut, sample FG 88-8b, GSC 141405; (E) Cross-section of seed of the same type as shown in D, Beaver Pond, sample FG 88-8b, GSC 141406.
Comparison of Drug Prescribing Before and During the COVID-19 Pandemic - A Cross-national European Study. Pharmaceuticals Consumption data
<p>Data and code supporting the article:</p> <p><strong>Comparison of Drug Prescribing Before and During the COVID-19 Pandemic - A Cross-national European Study </strong></p> <p>Prescription data from January 2017 to March 2021 for the Czech Republic, Germany, Lithuania, Slovenia, Spain (Catalonia), Sweden, and the United Kingdom (Scotland).<br>Data include the codes of the Anatomical-Therapeutic-Chemical classification (ATC) and corresponding numbers of dispensed defined daily doses (DDDs) and packs, aggregated by country, month and ATC.</p> <p>For more information, see the accompanying document ReadMe.txt.</p>
A rainfall data inter-comparison dataset for Germany
<p>The rainfall data inter-comparison dataset is a collection of precipitation statistics calculated from the hourly nationwide German radar climatology (RADKLIM) and radar online adjustment (RADOLAN) composites provided by the German Weather Service (Deutscher Wetterdienst, DWD), which were combined with rainfall statistics derived from rain gauge data for inter-comparison. Moreover, additional information on parameters that can potentially influence radar data quality, such as the height above sea level, information on wind energy plants and the distance to the next radar station, were included in the dataset.</p> <p>The dataset consists of two point shapefiles which are readable with all common GIS. It constitutes a spatially highly resolved rainfall statistics geodataset for the period 2006 - 2017, which can be used for statistical rainfall analyses or for the derivation of model inputs. Furthermore, this data collection has the potential to benefit all users who intend to use precipitation data for any purpose in Germany and to identify the rainfall dataset that is best suited for their application by a straightforward comparison of three rainfall datasets without any tedious data processing and georeferencing.</p> <ul> <li>Spatial extent: Germany</li> <li>Spatial Resolution: 1 x 1 km</li> <li>Time period: 2006 - 2017</li> <li>Data Format: Two point shapefiles</li> <li>Compared precipitation datasets: RADKLIM, RADOLAN, rain gauge data</li> <li>Selection of calculated precipitation statistics: <ul> <li>Annual precipitation sum</li> <li>Mean annual precipitation sum</li> <li>Mean seasonal precipitation sums</li> <li>Number of days exceeding a daily precipitation of 1 mm</li> <li>Number of days exceeding a daily precipitation of 20 mm</li> <li>Mean daily precipitation sum of all days exceeding a precipitation sum of 1 mm</li> <li>Mean daily precipitation sum of all days exceeding a precipitation sum of 20 mm</li> <li>Number of NoData entries</li> </ul> </li> </ul> <p>An Excel file with detailed information on all parameters and on original data sources is also included in the dataset.</p> <p>Original data source URLs:</p> <ul> <li>RADKLIM (DWD): https://opendata.dwd.de/climate_environment/CDC/grids_germany/hourly/radolan/reproc/2017_002/bin/</li> <li>RADOLAN (DWD): ftp://ftp-cdc.dwd.de/pub/CDC/grids_germany/hourly/radolan/historical/bin/</li> <li>Rain Gauge Data (DWD): https://opendata.dwd.de/climate_environment/CDC/observations_ germany/climate/1_minute/precipitation/</li> <li>Location of wind energy plants (UFZ): https://www.ufz.de/record/dmp/archive/5467/de/</li> <li>SRTM DEM (DLR): https://geoservice.dlr.de/egp/</li> </ul>
A comparison of automatic cell identification methods for single-cell RNA-sequencing data
<p>Benchmark datasets used to evaluate the performance of 22 classifiers for cell type classification for scRNA-seq data</p>
Data from Churan et al. 2018 Comparison of the precision of smooth pursuit in humans and head unrestrained monkeys
<p>Experiments were performed in two rhesus monkeys, B and E. Each monkey made a combination of slow and fast eye-movements following a visual target. The target was stationary at first and then either abruptly started moving (at a speed of 10°/s) in a certain direction (Ramp paradigm) or made a Step before starting the motion (Step-Ramp paradigm). By using a specific Step size and Step direction the initial saccade was eliminated in the Step-Ramp paradigm. The direction of the stimulus motion was predominantly horizontal with a smaller vertical component that was systematically varied between 0° and +-20°. We investigated how precisely the monkeys can follow this vertical component of the stimulus motion.</p> <p><strong>The files:</strong></p> <p>There are separate files for each monkey (B and E) and paradigm (Ramp and Step_Ramp). The files are MATLAB data files.</p> <p>Ramp:</p> <p>Each file consists of three variables – ‘alldatx’, ‘alldaty’, and ‘init’.</p> <p>‘alldatx’ and ‘alldaty’ are cell arrays in which each cell represents one vertical component of the stimulus: 1=20° up, 2=10° up, 3=5° up, 4=2° up, 5=0° , 6=2° down, 7=5° down, 8=10° down, 9=20° down. Each cell contains a matrix of n x 2001 elements. Each row represents the eye velocities during one individual trial between 1000 ms before and 1000 ms after the start of stimulus motion with a sampling rate of 1000 Hz.</p> <p>‘init’ is a cell array in which each cell represents one vertical component of the stimulus (s. above). Each cell contains a structure array which shows the approximate properties of the initial saccade in each trial:</p> <p>‘init.t’: Start end end time of the saccade (in ms) after the start of stimulus motion.</p> <p>‘init.amp’: Amplitude of the initial saccade in deg</p> <p>‘init.startpos’, ‘init.endpos’: start- and end-position (x, y) of the saccade</p> <p>Step_Ramp:</p> <p>Each file consists of two variables – ‘alldatx’, ‘alldaty’. Description is the same as for Ramp.</p>
MinION sequence data: MinION sequencing of colorectal cancer tumor microbiomes – a comparison with amplicon-based and RNA-Sequencing
<p>MinION sequencing data that was unmapped by minimap2 for the 11 samples using in the "MinION sequencing of colorectal cancer tumor microbiomes – a comparison with amplicon-based and RNA-Sequencing" paper.</p>
ScienceDex guides
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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.