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579 results for “Stratification”
Phenological changes in stratification and overturning of Northern Hemisphere ice-covered lakes
<p>The data and codes to reproduce analysis and visualization in the paper entitled "Projected phenological shifts in stratification and overturning of ice-covered Northern Hemisphere lakes"</p>
Dataset for "Winter inverse lake stratification under historic and future climate change"
<p>Summary results for Woolway et al., Winter inverse lake stratification under historic and future climate change. See README file for specific information on the variables provided.</p>
Unraveling the effects of cold stratification and temperature on the seed germination of invasive Spartina alterniflora across latitude
<p>Seed germination is critical to the life history of plants, playing an important role in the successful recruitment, colonization, and even invasion of new individuals within and outside population distribution ranges. Cold stratification and temperature are the key factors affecting seed germination traits. Studying how these two factors drive geographical variation in seed germination is essential to analyze and predict the geographical distribution range of alien plants in novel habitats. <em>Spartina alterniflora</em>, native to the United States, was introduced into China in 1979 and has spread over 20° of latitude along the eastern coast of China. Germination plays a crucial role in <em>S</em>. <em>alterniflora</em>'s large-scale invasion and diffusion across latitude. To evaluate the effects of cold stratification and temperature on seed germination of <em>S</em>. <em>alterniflora </em>across latitude, we collected seeds at seven locations across latitude in China. We exposed these provenances to cold stratification at 4°C (0, 1, 3, and 5 months) and germination temperature (5°C, 15°C, 25°C, and 35°C) treatments in growth chambers. Seed germination was observed for 98 days, and we calculated germination rate, germination index, and germination time. Results indicated that longer cold stratification significantly promoted germination rate and germination index, but decreased germination time. Similarly, higher germination temperature significantly promoted germination rate and germination index, but decreased germination time. Moreover, there were significant interactive effects on germination traits between cold stratification and temperature. Seed germination traits showed linear relationships with latitude, indicating that <em>S</em>. <em>alterniflora </em>seeds from different provenances germinated at different times and adopted different germination strategies. The stratification and temperature are the most important factors regulating the dormancy and germination seeds, so they can be important drivers of this variation along latitude. Under scenarios of warmer regional temperature, seeds at higher latitudes could germinate earlier and higher germination rate, which would favor a potential northern expansion of this invasive plant.</p>
Three-dimensional stratification pattern in an old-growth lowland forest: how does height in canopy and season influence temperate bat activity?
<p class="PaperLauftext">The study of animal-habitat interactions is of primary importance for the formulation of conservation recommendations. Flying, gliding and climbing animals have the ability to exploit their habitat in a three-dimensional way and the vertical canopy structure in forests plays an essential role for habitat suitability. Forest bats as flying mammals may seasonally shift their microhabitat use due to differing energy demands or changing prey availability, but the patterns are not well understood.</p> <p>We investigated three-dimensional and seasonal habitat use by insectivorous bats in a temperate lowland old-growth forest, the <i>Belovezhskaya Pushcha</i> in Belarus. We acoustically sampled broadleaved and mixed coniferous plots in the forest interior and in gaps in three heights during two reproductive periods (pregnancy/lactation versus post-lactation). In canopy gaps, vertical stratification in bat activity was less pronounced than in the forest interior. Vertical activity patterns differed among species. The upper canopy levels were important foraging habitats for the open-space forager guild and for some edge-space foragers like the Barbastelle bat <i>Barbastella barbastellus</i> and the soprano pipistrelle <i>Pipistrellus pygmaeus</i>. <i>Myotis</i> species had highest activity levels near the ground in forest gaps. Moreover, we found species-dependent seasonal microhabitat shifts. Generally, all species and species groups considered except <i>Myotis</i> species showed higher activity levels during post-lactation. <i>Myotis</i> species tended towards higher activity in the forest interior during post-lactation. <i>P. pygmaeus</i> switched from high activity levels in the upper canopy during pregnancy and lactation to high activity levels near the ground during post-lactation. We conclude that a full comprehension of forest bat habitat use is only possible when height in canopy and seasonal patterns are considered.</p>
Data for "The APC-Barrier and its effect on stratification in open access publishing"
<p>Dataset to reproduce the analysis of the paper "The APC-Barrier and its effect on stratification in open access publishing". An earlier version of the manuscript with the title "The APC-Effect: Stratification in Open Access Publishing" is available at <a href="https://doi.org/10.31222/osf.io/w5szk">https://doi.org/10.31222/osf.io/w5szk</a>.</p> <p>Data is licensed under CC-BY-SA International (4.0), see the file LICENSE.</p> <p>A full description of the dataset is provided in the README.md.</p>
Benchmark cancer datasets for Clustering algorithms for Omics-based Patient Stratification (COPS)
<p>This repository contains seven multi-omic cancer datasets including several cancer types (breast, kidney, lung, ovary, prostate, and thyroid cancers as well as low grade gliomas) that were used for benchmarking several multi-view clustering algorithms implemented by COPS (https://github.com/UEFBiomedicalInformaticsLab/COPS). The datasets were originally compiled from The Cancer Genoma Atlas (TCGA) and downloaded using the <em>curatedTCGAData</em> R-package. The datasets include copy-number variations, methylomics as well as mRNA and miRNA transcriptomics. The methylomics data was mapped to genes by averaging methylation level of probes associated with the promoter regions of genes. Similarly the miRNA transcriptomics data was mapped to genes by using known and predicted miRNA -> gene interactions. Updated survival data was acquired from the Liu et al. 2018 paper. </p> <p>This repository also includes two sets of cancer associated pathway networks used by pathway-based multi-omic methods benchmarked in our study. NCI-PID pathways were downloaded using the <em>ndexr</em> R-package on December 22 2021. While KEGG pathways were downloaded using the <em>pathview</em> R-package on May 3 2022. </p> <p>More details on the processing can be found on the related publication.</p>
Microclimate stratification in modified forests
<b>Description: </b><p>Microclimate datalogger recordings along a gradient from forest floor to forest canopy</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/111"><b>Microclimate stratification in modified forests</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=102">here</a></p><p><b>Files: </b>This consists of 1 file: template_HardwickVerticalStratification.xlsx</p><p><b>template_HardwickVerticalStratification.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Site information</b> (described in worksheet SitesGuide)</p><p>Description: Location of mciroclimate monitoring sites in relation to nearest forest edge</p><p>Number of fields: 3</p><p>Number of data rows: 12</p><p>Fields: </p><ul><li><b>Name</b>: Site of the measurement (Field type: Location)</li><li><b>EdgeDistance</b>: Distance of site from nearest edge. NB: sites with '200m' are a minimum, estimated distance - sites may have been further way; these sites are referred to as 'CORE' and were used as control sites for analysis (Field type: Numeric)</li><li><b>TreeHeight</b>: Height of the tree (Field type: Numeric)</li></ul></li><li><p><b>Microclimate stratification</b> (described in worksheet microclimate)</p><p>Description: Microclimate datalogger recordings along a gradient from forest floor to forest canopy</p><p>Number of fields: 8</p><p>Number of data rows: 290605</p><p>Fields: </p><ul><li><b>Plot</b>: Site of microclimate measurement (Field type: Location)</li><li><b>Height</b>: Height above ground. NB: Negative values indicate belowground sites (Field type: Numeric)</li><li><b>TreeTop</b>: Top of tree canopy? (Field type: Categorical)</li><li><b>time</b>: Date and time of microclimate reading (Field type: Datetime)</li><li><b>Temp</b>: Temperature (Field type: Numeric)</li><li><b>RH</b>: Relative humidity (Field type: Numeric)</li><li><b>LoggerType</b>: Brand of datalogger being used (Field type: Categorical)</li><li><b>LoggerID</b>: Serial number of the datalogger used to record microclimate (Field type: ID)</li></ul></li></ol><p><b>Date range: </b>2013-06-22 to 2015-10-28</p><p><b>Latitudinal extent: </b>4.6837 to 4.6839</p><p><b>Longitudinal extent: </b>117.5859 to 117.5863</p>
Data for "Trend and variability in global upper-ocean stratification since the 1960s"
<p>Abstract of associated paper: Many studies on future climate projection point out that, with progressing of global warming, upper-ocean stratification will strengthen over this century and consequently global-averaged ocean primary production will decrease. Observed long-term changes in the stratification to date, however, still show large uncertainties of the change itself and its driver. Focusing on the vertical difference in the emergence of the global warming signals, we used only observational profiles to describe the spatiotemporal characteristic of long-term trend and variability in the upper-ocean stratification. Rapid strengthening of the stratification (defined as the density difference between the surface and 200 m depth) since the 1960s was detected over most of the global ocean. Although the global average increase over 58 years (1960–2017) corresponds to 3.3–6.1% of the mean stratification, these strengthening trends considerably change depending on the regions. In addition to the well-documented explanation of strengthening stratification, namely that the surface intensification of global warming signal, we found that changes in subsurface temperature and salinity stratification associated with changes in atmospheric/ocean circulations and the global water cycle significantly contribute to the long-term change in the stratification and setting its regional difference. In mid- and high-latitude ocean of the northern hemisphere, the long-term trend in density stratification has noteworthy seasonality, which shows faster increase in boreal summer than that in winter. From the detrended time series, interannual variabilities correlated with a particular climate mode are detected in several ocean regions, suggesting that these variabilities are mainly driven by associated sea surface temperature variation.</p>
Forest plot: Associations between BMI at baseline and pCR following NACT – stratification according to ER status.
<p>Forest plot: Associations between BMI at baseline and pCR following NACT – stratification according to ER status.</p>
Near-bed stratification controls bottom hypoxia in ice-covered alpine lakes
<p>Dataset supporting the study of the development of near-bottom hypoxia in high-altitude lakes.</p> <p>Herein, hypoxia is set for dissolved oxygen concentrations equal to or below 2 mg/l</p> <p>Variables: Lake (name of the lake), Year (corresponding winter of measurements),Max_depth (lake'smax depth, in m),Lake_surface (lake's surface area in m2), Drainage_ratio (unitless), Percent_macrophyte_cover (lake's average macrophyte cover, in %), Catchement_NDVI (unitless),Secchi (Secchi depth in m, measured over the previous summer), ice_duration (estimated duration of the ice cover, in days), T_ice_on (average water column temperature at the date of ice_on, in °C), DOinit (average concentration in dissolved oxygen at ice-on, in mg/l), DOinitsat (average saturation in dissolved oxygen_DO_ at ice-on, in %), time_under_hypoxia (duration in days of near-bottom hypoxia under the ice), time_to_hypoxia (time in days to reach near-bottom hypoxia under the ice, after the onset of ice), Kexp (near_bottom DO decay rate under the ice, in /d), Klm (rate of near_bottom DO decrease under the ice, in mg/l/d), Kheat (deep warming rate under the ice, in /d).</p> <p>see the corresponding paper for more details</p> <p> </p>
Data for 'Surface heat fluxes drive a two-phase response in Southern Ocean mode water stratification'
<p>The files contained here are the output/sensitivity files of four adjoint sensitivity experiments in ECCOv4r2 that are combined to create the sensitivity of large-scale stratification to surface heat flux. (-f/Delta z) * (-alpha * (ADJqnet_t1 - ADJqnet_t2) + beta * (ADJqnet_s1 - ADJqnet_s2)) (Equation 7 in paper, where C = net heat flux). The files contained here are the output/sensitivity files for 6 years at 14 day time steps.</p> <p>ADJqnet_t1: (d J_1(theta_u)/ d qnet), Sensitivity of potential temperature over the upper depths to net heat flux.</p> <p>ADJqnet_t2: (d J_2(theta_l)/ d qnet), Sensitivity of potential temperature over the lower depths to net heat flux.</p> <p>ADJqnet_s1: (d J_3(salt_u)/ d qnet), Sensitivity of salinity over the upper depths to net heat flux.</p> <p>ADJqnet_s2: (d J_4(salt_l)/ d qnet), Sensitivity of salinity over the lower depths to net heat flux.</p> <p> </p> <p>Paper Abstract: Subantarctic mode waters (SAMW) have low stratification and are formed through subduction from thick winter mixed layers in the Southern Ocean. To investigate how external forcing affects the stratification in mode water formation regions in the Southern Ocean, we conduct a set of adjoint sensitivity experiments. The objective function is the annual-average stratification over the mode water formation region, which is evaluated from potential temperature and salinity adjoint sensitivity experiments. The analysis of impacts, from the product of sensitivities and forcing variability, identifies the separate effects of the wind stress, heat flux, and freshwater flux, revealing that the dominant control on stratification is from surface heat fluxes, as well as a smaller effect from zonal wind stress. The adjoint sensitivities of stratification to surface heat flux reveal a surprising change in sign over 2 years lead time. Surface cooling leads to the expected initial local decrease in stratification. However, there is a delayed response to surface cooling leading to an increase in stratification. This delayed response in stratification involves atmospheric damping of the surface thermal contribution, so that eventually the oppositely-signed advective haline contribution dominates. This two-phase response of stratification is found to hold over mode water formation regions in the South Indian and Southeast Pacific sectors of the Southern Ocean, where there are strong advective flows linked to the Antarctic Circumpolar Current.</p>
Stratification reference points for Luhansk region tree cover change (1996,2000,2013,2020)
<p><strong>Occupation of Environment: Long-Term Consequences of war in Ukraine on conservation of forested areas of Emerald Network in the Luhansk region - </strong>Generated sample points that reflect stratification type and landcover change for Luhansk region for tree cover change area estimation. The division into territories controlled by Ukraine and Russia made based on the demarcation line with consideration of the buffer zone, where Ukrainian institutions were disconnected due to the active warfare in purpose of separation of zones with interruption of Ukrainian environmental policies.</p>
Luhansk Region Tree Cover Change Stratification Map (1996-2020)
<p>Luhansk region tree cover change stratification map created based on the tree cover masks for Luhansk region for 1996, 2000, 2013 and 2020 with 30 m. spatial resolution. Strata classes: 1 - Stable forest, 2 - Forest change, 3 - Stable not forest</p>
Next Generation Sequencing-Based Stratification of Front Line Treatment of HighGrade Neuroendocrine Carcinoma
ClinicalTrials.gov study NCT04452292. IPD Sharing: NO. Countries: 1. Publications: 1.
Lung Elastrosonography in Diagnosis and Stratification of COPD and Fibrosis
ClinicalTrials.gov study NCT04149652. IPD Sharing: NO. Countries: 1. Publications: 10.
Effect of Providing Stratification of Low Risk Penicillin Allergies on Penicillin Allergy Label Removal in ICU Setting
ClinicalTrials.gov study NCT03702283. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
CARISMA : Cardiac Arrhythmias and Risk Stratification After MyoCardial Infarction
ClinicalTrials.gov study NCT00145119. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Developing and Evaluating a Machine-Learning Opioid Overdose Prediction & Risk-Stratification Tool in Primary Care
ClinicalTrials.gov study NCT06810076. IPD Sharing: NO. Countries: 1. Publications: 5.
Early Risk Stratification in ED Chest Pain Patients
ClinicalTrials.gov study NCT02364271. IPD Sharing: Not stated. Countries: 1. Publications: 17.
A Phase II Study to Evaluate Axumin PET/CT for Risk Stratification for Prostate Cancer
ClinicalTrials.gov study NCT03373006. IPD Sharing: YES. Countries: 1. Publications: 5.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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DANDI Archive for NWB datasets
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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.