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13,021 results for “Localization”
Tree seedling abundance mediated by local neighborhood effects and microsite conditions
Tree recruitment across elevational gradients is shaped by myriad factors, including abundance of nearby conspecific adults and abiotic establishment conditions. We measured seedling abundance and overstory basal area for six tree species that dominate northern temperate and montane boreal forests on mountains in the northeastern United States. Data were collected on elevational transects spaced at 100m-intervals of elevation on ten mountains. Associated environmental variables, including vegetation cover, substrate, microclimate, and light environment, were also collected.
newbi4fmri2020 Localizer
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Auditory localization with 7T fMRI
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NeuroSpin hMT+ Localizer DATA (MEG & aMRI)
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Database of local seismicity registered on ocean bottom seismometers (OBS). Database related to Bornstein et al. (accepted in Earth and Space Science), PICKBLUE
<p>We assembled a database of Ocean Bottom Seismometer (OBS) waveforms and manual P and S picks from local seismicity, on which we trained PickBlue, a deep-learning picker, using the seismometer data and the hydrophone channel. The dataset belongs to Bornstein et al. (accepted 2023 in Earth and Space Science). The picker and database are available in the SeisBench platform, allowing easy and direct application to OBS traces and hydrophone records.</p><p>The complete database is also accessible with SEISBENCH: <br><a href="https://seisbench.readthedocs.io">https://seisbench.readthedocs.io</a><br>SEISBENCH on github:<br><a href="https://github.com/seisbench">https://github.com/seisbench</a></p><p>Related paper:</p><p>Bornstein, T., Lange, D., Münchmeyer, J., Woollam, J., Rietbrock., A., Barcheck, G., Grevemeyer, I., Tilmann, F. (accepted 2023 in Earth and Space Science). PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning, Earth and Space Science. </p>
DNA Origami Raw AFM Data - NanoLocz: Image analysis platform for AFM, high-speed AFM and localization AFM
<p>The data file is in the original ARIS data format as captured on a Cypher VRS1250 AFM (Oxford Instruments)<br><br><br></p>
The local extinction of Cedrus atlantica in the Iberian Peninsula could have been completed due to biological interaction
<p>This data set is used to explore the possibility that <em>Cedrus atlantica</em> (Endl.) Carrière and <em>Pinus nigra</em> Arnold could have interacted in the past, mutually excluding each other in the areas with suitable conditions for both species and, where, ultimately, the one that was most competitive would remain. The species show very well differenciated niches and a distribution of their habitats segregated by continents (<em>P. nigra</em> in Europe and <em>C. atlantica</em> in Africa), which responds to differences in climatic affinities. However, the contact of their distributions in bordering areas suggests that <em>C. atlantica</em> maintained its presence in the Iberian Peninsula until recent times, and that <em>P. nigra</em> could have displaced it due to its higher prevalence on the continent.</p>
Pawpaws prevent predictability: A locally-dominant tree alters understory beta-diversity and community assembly
<p>Data used in "Pawpaws Prevent Predictability: A locally-dominant tree alters understory beta-diversity and community assembly" (Wassel and Myers) accepted for publication in Ecosphere.<br><br><strong>Metadata for Zenodo.pdf </strong>contains more information on the following data files including descriptions of the columns. </p> <p>The file <strong>understory_abundance_data2021.csv</strong> contains all species abundances in 1x1m plots. This data was used for analyses in publication. Each row is a plot, each column is a speceis or plot descriptor, values for columns 5 and higher are species abundances. Data was collected July-August 2021 by Anna Wassel in Missouri, USA. </p> <p>The file <strong>understory_species_list2021.csv </strong>contains a list of the species codes used in the first file with their scientific names and their status as herbs or woody. This was used to filter out herbaceous species from the data set for herbaceous-only analyses. </p> <p> </p>
Accounting for local temperature effect substantially alters afforestation patterns - data
<p>Output data produced in "Accounting for local temperature effect substantially alters afforestation patterns"</p> <p>Contact: michael.gregory.windisch@alumni.ethz.ch</p> <p>Content: Output of the partial equilibrium model MAgPIE (https://github.com/magpiemodel/magpie) version v4.3.1-BGP (https://github.com/magpiemodel/magpie/tree/v4.3.1-BGP) documentation (<a href="https://rse.pik-potsdam.de/doc/magpie/4.3.1/">https://rse.pik-potsdam.de/doc/magpie/4.3.1/</a>). Archived are all runs performed to obtain data and figures for the main assessment (main_output.zip) and the two sensitivity experiments (sensitivity_output_globalTCRE.zip; sensitivity_output_plantation.zip).</p> <p> </p> <p>Naming key:</p> <p>main_output control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS</p> <p>main_output experiment runs: BPHfillexp_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS</p> <p>sensitivity analysis for global TCRE control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS</p> <p>sensitivity analysis for global TCRE experiment runs: BPHfillexp_ann_bph_{SSP}_global_{TCRE uncertainty}_noBECCS</p> <p>sensitivity analysis for plantation A/R control runs: BPH_plant_nobgp_{SSP}_noBECCS</p> <p>sensitivity analysis for plantation A/R experiment runs: BPH_plant_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS</p>
Bluetooth indoor localization Dataset
<p><strong>Bluetooth indoor localization Dataset</strong>: Collected to perform experimentation on how bluetooth signal strengths can be used to determine one of the indoor locations. The dataset has 6 transmission power, from Tx01 to Tx06; and in each dataset have 5 features with the bluetooth RSSI because the enviroment have 5 BLE4.0 and 1 categorical target that is the sector where the person is located (15 sectors total).</p>
Dataset of "The Impact of Local Strain Fields in Noncollinear Antiferromagnetic Films"
<p>Antiferromagnets hosting structural or magnetic order that breaks time reversal symmetry are of increasing interest for “beyond von Neumann” computing applications because the topology of their band structure allows for intrinsic physical properties, exploitable in integrated memory and logic function. One such group are the noncollinear antiferromagnets. Essential for domain manipulation is the existence of small net moments found routinely when the material is synthesized in thin film form and attributed to symmetry breaking caused by spin canting, either from the Dzyaloshinskii–Moriya interaction or from strain. Although the spin arrangement of these materials makes them highly sensitive to strain, there is little understanding about the influence of local strain fields caused by lattice defects on global properties, such as magnetization and anomalous Hall effect. This premise is investigated by examining noncollinear antiferromagnetic films that are either highly lattice mismatched or closely matched to their substrate. In either case, edge dislocation networks are generated and for the former case, these extend throughout the entire film thickness, creating large local strain fields. These strain fields allow for finite intrinsic magnetization in seemingly structurally relaxed films and influence the antiferromagnetic domain state and the intrinsic anomalous Hall effect. The dataset consists of total energies calculated by density functional theory (VASP). The experimental data presented in the paper were obtained by international partners not supported by OP-JAK project.</p>
Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux -- Supplemental Data Set: Sea Level Sensitivity Kernels
<p><strong>Quantifying the Sensitivity of Sea Level Change in Coastal Localities to the Geometry of Polar Ice Mass Flux<br> SUPPLEMENTAL DATA SET: SEA LEVEL SENSITIVITY KERNELS</strong></p> <p>To accompany</p> <p> Jerry X. Mitrovica, Carling C. Hay, Robert E. Kopp, Christopher Harig, and<br> Konstantin Laytchev (2018). Quantifying the Sensitivity of Sea Level Change<br> in Coastal Localities to the Geometry of Polar Ice Mass Flux. Journal of<br> Climate. doi: 10.1175/JCLI-D-17-0465.1.</p> <p>We provide sea level kernels for ~740 tide gauge sites in the Permanent Service for Mean Sea Level (PSMSL) database (Holgate et al., 2013). Kernels associated with sensitivities to Greenland and Alaskan glacier melt are given on a spatial grid covering the globe, with 512 latitude rows (i=1,512) and 1024 longitude (j=1,1024) columns.</p> <p>Longitude values are evenly spaced moving eastward from Greenwich (the jth grid point has an east longitude value of (j-1)×360°/1024). Latitude values are Gauss-Legendre points beginning close to the North Pole and ending near the South Pole. Kernels associated with sensitivities to Antarctic melt are given on a spatial grid covering the globe, with 256 (Gauss-Legendre) latitude rows (i=1,256) and 512 longitude (j=1,512) columns. Longitude values are evenly spaced moving eastward from Greenwich.</p> <p>The format of the files is: </p> <p> grid_sitenumber_region.txt</p> <p>where “region” is either “green” (Greenland), “ant” (Antarctic) or “Alaska” (Alaska). The list of sites (and site numbers) is provided in the sites.txt file. The first 8 sites in this list were test sites and can be ignored.</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>
CMIP6-based local-scale climate scenarios for impact assessment in Great Britain.
<p>Climate change impact assessments require local-scale climate scenarios. The climate change projections from <span>Global Climate Models (GCMs) </span>are difficult to use at local scale due to their <span>coarse spatial and temporal resolution. </span><span>It is important to have climate change scenarios based on GCMs climate projections GCMs ensembles, e.g. CMIP6, downscaled to local scale to account for their inherent uncertainty, and to generate a sufficient large number of </span>realisations <span>to account for inter-annual climate variability and low frequency but high impact extreme climatic events. A</span><span> <span>dataset of future climate change scenarios was therefore generated at </span></span><span>26 representative sites across the UK</span><span> based on the latest </span><span>CMIP6 multi-model ensemble </span><span>downscaled to local-scale by using a </span><span>stochastic weather generator LARS-WG 7.0. The data set provides </span><span>1,000 years of daily weather at each selected site for a baseline (1985-2015), and very near- (2030) and near-future (2050) climate change scenarios, based on five GCMs and two emission scenarios (</span><span>Shared Socioeconomic Pathways - SSPs <em>viz</em>. </span>SSP2-4.5 and <span>SSP5-8.5)</span><span>.</span><span> </span><span>A total of </span>15 GCMs from the CMIP6 ensemble were integrated in LARS-WG 7.0. <span>LARS-WG downscales future climate projections from the GCMs and incorporates changes at local scale in the mean climate, climatic variability, and extreme events by modifying the statistical distributions of the weather variables at each site. </span>Based on the performance of the GCMs over northern Europe and their climate sensitivity, a subset of five GCMs was selected, <em>viz</em>.; ACCESS-ESM1-5, CNRM-CM6-1, HadGEM3-GC31-LL, MPI-ESM1-2-LR and MRI-ESM2-0. The selected GCMs are evenly distributed among the full set of 15 GCMs. The use of a subset of GCMs substantially reduces computational time, while allowing assessment of uncertainties in impact studies related to uncertain future climate projections arising from GCMs.<span> <span>The 1000 years of </span></span>realisations <span>of daily weather for the baseline as well as future climate change scenarios are helpful for estimating </span>seasonality and<span> inter-annual variation, and for detecting short, </span>low frequency but high impact extreme climatic signals, such as heat waves, floods and drought events. The dataset <span>can be used as an input to climate change impact models in various fields, including, </span><span>land and water resources, agriculture and food production, </span>ecology and epidemiology, and <span>human health and welfare. Researchers, breeders, farm and programme managers, social and public sector leaders, and policymakers may benefit from this new dataset when undertaking impact assessment of climate change and decision support for mitigation and adaptation.</span></p>
In vivo rat brain for Ultrasound Localization Microscopy: raw and beamformed data.
<p><strong>Datasets provided for Open Platform for Ultrasound Localization Microscopy: Performance Assessment of Localization Algorithms.</strong></p> <p><strong>Abstract:</strong></p> <p>Ultrasound Localization Microscopy (<strong>ULM</strong>) is an ultrasound imaging technique that relies on the acoustic response of sub-wavelength ultrasound scatterers to map the microcirculation with an order of magnitude increase in resolution. Initially demonstrated <em>in vitro</em>, this technique has matured and sees implementation<em> in vivo</em> for vascular imaging of organs, and tumors in both animal models and humans. The performance of the localization algorithm greatly defines the quality of vascular mapping. We compiled and implemented a collection of ultrasound localization algorithms and devised three datasets<em> in silico</em> and<em> in vivo</em> to compare their performance through 18 metrics. We also present two novel algorithms designed to increase speed and performance. By openly providing a complete package to perform ULM with the algorithms, the datasets used, and the metrics, we aim to give researchers a tool to identify the optimal localization algorithm for their usage, benchmark their software and enhance the overall image quality in the field while uncovering its limits.</p> <p>This article provides all materials and post-processing scripts and functions.</p> <p><strong>Methods:</strong></p> <p>200.000 ultrasound images have been acquired <em>in vivo </em>on a rat brain with skull removal at 1000 Hz with a 15 MHz linear probe.</p> <p>This dataset contains raw radiofrequency data (<strong>RF</strong>) and beamformed images (<strong>IQ</strong>) of the brain vascularization with flowing microbubbles (ultrasound contrast agent).</p> <p><strong>Article to be cited:</strong> Heiles, Chavignon, Hingot, Lopez, Teston and Couture.<br> <a href="http://doi.org/10.1038/s41551-021-00824-8"><em>Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy</em>, Nature Biomedical Engineering, 2022, (doi.org/10.1038/s41551-021-00824-8)</a>.</p> <p><strong>Related processing scripts and codes:</strong> <a href="https://github.com/AChavignon/PALA">github.com/AChavignon/PALA</a></p> <p><strong>Related datasets:</strong> <a href="https://doi.org/10.5281/zenodo.4343435">doi.org/10.5281/zenodo.4343435</a></p> <p><strong>Acknowledgments:</strong></p> <p>We thank Cyrille Orset (INSERM UMR-S U1237, Physiopathology and Imaging of Neurological Disorders, GIP Cyceron, BB@C, Caen, France) for animals’ preparation and perfusion of contrast agent and the biomedical imaging platform CYCERON (UMS 3408 Unicaen/CNRS, Caen, France).</p>
Local scale carbon and nitrogen cycling in temperate forests, eastern U.S., 2017-2018
Data collected in 2017-2018 from individual mature canopy trees (and their surrounding soil) and from monospecific common garden plots to assess how aboveground and belowground carbon and nitrogen cycling are related. Data include foliar, litter, root, and soil carbon and nitrogen pools and fluxes. Field sites span the eastern United States, including south-central Indiana (Moores Creek), Maryland (Smithsonian Environmental Research Center), Pennsylvania (Pennsylvania State University common garden), and Massachusetts (Harvard Forest).
Mangrove leaf physiological response to local climate at Key Largo, Watson River Chickee, Taylor Slough, and Little Rabbit Key, South Florida (FCE) from July 2001 to August 2001
Determine the red mangrove leaf physiological response to the local climate to understand the local controls on plant physiology. Data were collected in the Key Largo Ranger Station, Watson River Chickee and Taylor Slough research Sites, South Florida.
Locally verified daily temperature and precipitation data from a NOAA weather station at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1914-2006
This data package contains locally verified daily meteorological observations from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. Daily data has been collected there by USDA staff since 1914 for minimum and maximum air temperature and daily accumulated precipitation using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from the original paper data sheets and have undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. Local verification and transcription of observations from the data sheets ceased in 2006 and data are now directly entered to the NOAA system. Therefore, this dataset is complete and will no longer be added to. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal (https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USC00294426/detail - daily and monthly data are available).
Locally verified monthly summary temperature and precipitation data from a NOAA weather station at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1914-1998
This data package contains locally verified monthly meteorological observations from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. Monthly summary data (based on daily observations) has been collected there by USDA staff since 1914 for minimum and maximum air temperature and daily accumulated precipitation using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from the original paper data sheets and have undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. Local verification and transcription of observations from the data sheets ceased in 1998 and data are now directly entered to the NOAA system. Therefore, this dataset is complete and will no longer be added to. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal https://www.ncdc.noaa.gov/cdo-web/datasets/GSOM/stations/GHCND:USC00294426/detail - daily and monthly data are available).
Locally verified evaporation data from a NOAA evaporation pan at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1953-1979
This data package contains locally verified monthly total pan evaporation data from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. The evaporation pan measurements commenced in 1953 and ended in 1979 when the instrument was decommissioned. Pan evaporation observations were made using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from records retrieved from NOAA in ~1995 and have since undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. There is no further data from this decommissioned instrument, so this dataset is now complete and data will no longer be updated here. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal (https://www.ncdc.noaa.gov/cdo-web/datasets/GSOM/stations/GHCND:USC00294426/detail - monthly pan evaporation data are available back to 1930, but there may be data issues prior to 1953).
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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.