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3,145 results for “wells”
Brightfield images of cells and spheroids in wells annotated with bounding boxes
<p>The images in this dataset show cells in different developmental stages upon forming spheroids. They can go through several developmental sages: Starting from cells, they turninto compacted objects and then into spheroids. Ultimately, they can die and disintegrate. The objects are annotated with bounding boxes that carry these respective labels. The dataset in its current form can be upload to an OMERO server using the omero-cli-transfer package - simply download the zip file, log into your omero server and use the `omero transfer unpack` command as shown on the <a href="https://github.com/ome/omero-cli-transfer">omero-cli-transfer documentation</a>.</p> <p>The dataset can be used to train object detection models such as a <a href="https://docs.ultralytics.com/models/yolov8/">yolo classifier </a>- the linked repository provides a tutorial on how to do so.</p>
LivWell: a sub-national database on the Living conditions of Women and their Well-being for 52 countries
<p>LivWell is a global longitudinal database which provides a range of key indicators related to women’s socioeconomic status, health and well-being, access to basic services, and demographic outcomes. Data are available at the sub-national level for 52 countries and 447 regions. A total of 134 indicators are based on 199 Demographic and Health Surveys for the period 1990-2019, supplemented by extensive information on socioeconomic and climatic conditions in the respective regions for a total of 190 indicators. The resulting data offer various opportunities for policy-relevant research on gender inequality, inclusive development, and demographic trends at the sub-national level.</p> <p>For a full description, please refer to the article describing the database here: (link to come)</p> <p>The companion repository <em>livwelldata </em>allows to easily use the database in R. The R package can be downloaded following the instructions on the following git repository: https://gitlab.pik-potsdam.de/belmin/livwelldata. The version of the database in the package is the same as in this repository.</p>
Data on public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland
<p>A public participatory GIS -survey dataset detailing public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland.</p>
HyUSPRe Report & Data on 'New experimental data on reactions between H2 and well cement and effects on fluid flow and mechanical properties of well cement
<p>In this study, new experimental data is presented of the effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties of oil well (class G) cement, relevant for underground hydrogen storage operations. Changes in mechanical properties (Young’s modulus, Poisson’s ratio and ultimate strength) have been analyzed using unconfined compressive strength (UCS) tests and confined cyclic loading tests on class G cement samples that were unreacted (cured for 3 days at 80°C) and exposed to lime-saturated brine and N<sub>2</sub> or H<sub>2</sub> for 1 and 2 months. Changes in cement mineralogy were analyzed by XRD analysis of the unreacted and exposed samples. The mechanical properties of elastic modulus and Poisson’s ratio are within the expected range of an oil well cement. Differences in Young’s modulus, Poisson’s ratio and ultimate strength are limited between unreacted, N<sub>2</sub>-exposed and H<sub>2</sub>-exposed samples, when comparing UCS tests or confined cyclic loading tests. Repeated UCS tests seem to indicate that the variation in Young’s modulus and ultimate strength increases after N<sub>2</sub> and H<sub>2</sub> exposure, but this observation needs to be confirmed in additional tests. During cyclic axial loading of confined cement samples, irreversible (plastic) deformation (compaction) occurs that affect static Young’s modulus. Also, effects of exceeding yield and failure strength on Young’s modulus are observed. Dynamic Young’s moduli and Poisson’s ratios derived from acoustic velocity measurements during confined cyclic tests show limited variation, in particular if static and dynamic Young’s modulus are compared. The mineralogical changes as identified using XRD analysis suggest minor changes between unexposed and H<sub>2</sub>- and N<sub>2</sub>-exposed samples, although XRD patterns indicate some minerals that could not be identified. The main conclusion is that effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties and mineralogical changes of class G cement is limited compared to unreacted or N<sub>2</sub> exposed samples for the investigated conditions. There is no indication that changes in mechanical properties of cement are such that cement integrity of wells used for underground hydrogen storage will be significantly affected. It should be emphasized that this conclusion is based on experiments on one type of cement (class G) and a limited set of conditions. In particular, additional tests to assess the reproducibility of current results and tests on samples that were exposed longer to H<sub>2</sub> and N<sub>2</sub> are of interest. Detailed effects of changing properties for the durability and integrity of wells can be derived by performing a parameter sensitivity analysis with well integrity modelling for the range in mechanical properties measured in this study.</p>
Data for ECHAM-HAM in the Publication "Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions"
<p>This repository contains 3-hourly data of the ECHAM-HAM experiment in the paper:</p> <p>"Saponaro, G., Sporre, M. K., Neubauer, D., Kokkola, H., Kolmonen, P., Sogacheva, L., Arola, A., de Leeuw, G., Karset, I. H. H., Laaksonen, A., and Lohmann, U.: Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions, Atmos. Chem. Phys., 20, 1607–1626, https://doi.org/10.5194/acp-20-1607-2020, 2020."</p>
Data from "Examining potential PFAS Contamination of Private Wells from a High School in Rural Maine"
Data from "Schools as Sources of PFAS Contamination of private wells in Rural Maine communities" In a community-engaged research project near Mount Desert Island High School in Bar Harbor, Maine, efforts were made to understand potential well contamination. This involved attending public meetings, distributing PFAS drinking water sample kits to homeowners, and collaborating on sample collection protocols. Surface water samples were collected from wetlands adjacent to the school, while drinking water samples were obtained from eight property owners, with careful adherence to sampling procedures to prevent contamination. Samples were analyzed for PFAS content and data are reported here.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Bronco Well Meteorological Station (BRWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Bronco Well Meteorological Station (BRWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbrwl/. These data complement and extend meteorological data recorded by an adjacent station (Met45), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Burris Well Meteorological Station (BUWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Burris Well Meteorological Station (BUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbuwl/. These data complement and extend meteorological data recorded by an adjacent station (Met50), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Deep Well Meteorological Station (DPWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Deep Well Meteorological Station (DPWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetdpwl/. These data complement and extend meteorological data recorded by an adjacent station (Met40), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Test Well Meteorological Station (TSWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Test Well Meteorological Station (TSWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmettswl/. These data complement and extend meteorological data recorded by an adjacent station (Met52b), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Tule 222 Well Meteorological Station (TUWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Tule 222 Well Meteorological Station (TUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmettuwl/.
Groundwater nitrate concentrations in wells located at the shoreline of West Falmouth Harbor from 2006 to 2023
West Falmouth Harbor (West Falmouth, MA, USA) has been experiencing a dramatic increase in nitrogen loading from an upgradient municipal wastewater treatment facility since the early 2000's. As part of a long-term study into the effects of this nitrogen enrichment, we have been measuring groundwater chemistry in wells installed along the shoreline of the harbor to monitor the spatial and temporal patterns in N loading. Water samples were collected approximately annually from 2006 through 2009, and less frequently in subsequent years, and processed for nitrate + nitrite. Full analysis details are available in Hayn et al. 2025 in Estuaries and Coasts (doi: 10.1007/s12237-025-01630-0).
Unregulated Wells on the Navajo Nation Data Compilation
In the United States the use of unregulated water sources – defined as sources that do not meet criteria to be classified as a public water system as defined by the Safe Drinking Water Act - are used regularly for livestock watering, agriculture, domestic, and other purposes. Nationally, more than 45 million people rely on unregulated water sources for drinking water; however, there remains infrastructure disparities for drinking water access in communities on Tribal nations. For the Navajo Nation, a sovereign Indigenous nation in the Southwestern United States, between 7% and 30% of homes lack plumbing to deliver household drinking water, so residents are compelled to access other water sources – regulated and unregulated alike. Previous unregulated water quality studies on the Navajo Nation were regionally focused and unsuitable for evaluating water quality trends across the Navajo Nation, an area that encompasses more than 71,000 square kilometers in Arizona, New Mexico, and Utah. Therefore, beginning in 2011 the Community Environmental Health Program at the University of New Mexico began to compile existing water quality datasets, principally for unregulated groundwater sources, in a single geospatial relational database. Researchers at the University of New Mexico Center for Native Environmental Health Equity Research, University of New Mexico METALS Superfund Research Program, University of Arizona, Northern Arizona University, and the Southwest Research and Information Center have compiled a database of water quality measurements from groundwater wells on the Navajo Nation using data from the U.S. Geological Survey, U.S. Army Corps of Engineers, U.S. Centers for Disease Control and Prevention, Navajo Nation Environmental Protection Agency, and data from researchers at the University of New Mexico, Dine College and Northern Arizona University. To date, this data compilation has been used for publications but has not been disseminated publicly. The purpose of t
Photosynthetically Active Radiation data taken with the Delta-T SunScan wand every 15 cm of 1m x 1m chamber flux and point frame plots as well as four remotely monitored canopies at the Toolik Field Station in AK, Summer 2012.
Within-canopy PAR was measured with a Delta-T SunScan wand every 15 cm from the ground to above the canopy under both direct and diffuse light. The data includes all outputs from the SunScan wand: time of measurement, spread of PAR sensors, total irradiance, total diffuse light, and individual outputs of 64-PAR sensors on the SunScan wand. These measurements were taken for 1m x 1m chamber flux (n=14) and point frame (n=19) plots as well as sites four montitored remotely by PAR sensors located above, within, and below shrub canopies. All plots were dominated either by tall Salix pulchra and Betula nana species and were located near the LTER shrub plots at Toolik Field Station , AK in the summer of 2012.
Rain, well and river water oxygen and deuterium isotope analyses/values for Bonanza Creek Experimental Forest and LTTG sites ( 2002 - Present)
Isotope values for oxygen and hydrogen in waters provide information as to the source of the water, the climate at the time of collection, and the geographical location of the water source. Climate variations may be indicated in changes in the relationship between deuterium and 18O over an extended period. The sources and proportions of sources of ground water can be determined by isotope analysis. Rain, well and river waters were analyzed for ?18O and ?D values from LTER and LTTG sites in 2002, and LTER1, LTER2, UP2, and FP3 sites from 2003 on. Deuterium values were not replicable until the latter part of the 2005 field season and so were not reported until August, 2005.
Measurements from CalCOFI cruises in the California Current System, including log of station information, weather, sea conditions as well as physical, chemical and biological measurements including including temperature, salinity, oxygen, density, sigma theta, phosphate, silicate, nitrite, nitrate, ammonia, chlorophyll a, integrated chlorophyll a, primary productivity, and integrated primary production. 1949 - January 2020
Since 1949, hydrographic and biological data of the California Current System have been collected on quarterly CalCOFI cruises. The 59+ year hydrographic time-series includes weather, temperature, salinity, oxygen and phosphate observations. In 1961, nutrient analysis expanded to include silicate, nitrate and nitrite; in 1973, chlorophyll was added; in 1984, C14 primary productivity incubations were added. These data are being provided here in collaboration with CalCOFI-SIO in order to provide an additional queriable interface to the data. The data are updated on a regular basis from the CalCOFI hydrographic database.
Groundwater well chemistry from 7 Hillslope Project sites in Macon County, North Carolina, within the Upper Little Tennessee River Basin
Shallow groundwater wells were installed at 7 sites throughout Macon County, NC beginning in 2011. Sites represent a gradient of land use, including relatively undisturbed forests, valley bottomlands in agriculture, and mountain developments. Nine groundwater wells were placed along 3 "ridge-to-riparian" transects at each site. Collections were made every other week.
Groundwater well specifications from 9 Hillslope Project sites in Macon County, North Carolina, within the Upper Little Tennessee River Basin
The hillslope study was established to directly link land use impacts to streamwater quality in the southern Appalachian Mountains. Nine sites were selected in the Little Tennessee River watershed in Macon County, NC, representing four land use types: forest, mountain development, traditional valley, and large river valley. At each of these sites, three subsurface flowpaths were identified, and four plots were established along the flowpath following the elevation gradient. At seven of the nine sites, the three lower elevation plots at one of the subsurface flowpaths had ground water wells installed in order to measure groundwater stage along an elevational gradient. A total of 61 groundwater wells were installed and their depths recorded.
Manual well measurements from 9 Hillslope Project sites located in Macon County, North Carolina, within the Upper Little Tennessee River Basin
The hillslope study was established to directly link land use impacts to streamwater quality in the southern Appalachian Mountains. Nine sites were selected in the Little Tennessee Riverwatershed in Macon County, NC, representing four land use types: forest, mountain development,traditional valley, and large river valley. At each of these sites, three subsurface flowpathswere identified, and four plots were established along the flowpath following the elevation gradient. At seven of the nine sites, the three lower elevation plots at each of the subsurface flowpaths had ground water wells installed in order to measure groundwater stage along an elevational gradient. Measurements were taken every two weeks. Water depth in these wells was manually measured every two weeks using a water level indicator. Please see the accompanying well construction data for additional groundwater well information.
Groundwater well chemistry data for Niwot Saddle, C1 and Martinelli, 2005 - ongoing.
This is a summary of major ion concentrations and chemistry data for groundwater samples collected at groundwater wells on the Niwot saddle, C1 site and Martinelli site.
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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.