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19,796 results for “stem”
Above ground plant and below ground stem biomass in the Arctic LTER acidic tussock tundra experimental plots, 2002, Toolik Lake, Alaska.
Above ground plant and below ground stem biomass and their carbon and nitrogen content was measured in the Arctic LTER moist acidic tussock tundra experimental plots(MAT89). Treatments included control, nitrogen plus phosphorus amended plots for either 6 or 13 years and vole exclosure plots with or without amends of nitrogen and phosphorus. Note: The added Carbon and Nitrogen values were incorrectly added to the data sheet. A block of data was repeated for all treatments. In version 14 the values were corrected.
Above ground plant, belowground stem and root biomass in Arctic Long-term Ecological Research's 2006 moist acidic tussock tundra experimental sites, 2012, Toolik Lake, Alaska.
Above ground plant, belowground stem and root biomass was measured in moist acidic tussock tundra experimental sites established in 2006 by the Arctic Long-term Ecological Research site (ARC-LTER. Control plots and plots amended with three different levels of nitrogen(N) and phosphorus(P), F10 (10 g/m2 N and 5 g/m2 P); F5 (5 g/m2 N and 2.5 g/m2 P); F2 (2 g/m2 N and 1 g/m2 P), were sampled.
Above ground plant and below ground stem biomass of samples from the unburned control site near the Anaktuvuk River fire scar.
Above ground plant and below ground stem biomass were measured in 2011 from three sites at and around the Anaktuvuk River Burn: severely burned, moderately burned and unburned. These samples were analyzed for carbon and nitrogen concentrations.
Above ground plant and below ground stem biomass of samples from the severely burned site of the Anaktuvuk River fire, Alaska
Above ground plant and below ground stem biomass were measured in 2011 from three sites at and around the Anaktuvuk River Burn: severely burned, moderately burned and unburned. These samples were analyzed for carbon and nitrogen concentrations.
WPE02 Shrub stem data to quantify woody encroachment in Konza watersheds from 2020, 2022, and 2023
Woody plant encroachment (WPE) is one of the most widespread and acute threats affecting grasslands worldwide. Nature-based solutions to reversing WPE in mesic grasslands have proven largely ineffective, with decades of frequent prescribed fire failing to reverse WPE in some instances. One solution is to conduct more extreme fires compared to traditional prescribed fire. However, most tests of this idea have occurred at small scales, a mismatch with the need for landscape-scale land management. We considered two catchments, each with long-term destocking of grazers to increase fuel loads, one which accidentally burned under dry windy conditions that produced an extreme fire, while one burned under prescribed fire conditions. The extreme fire caused a sharp decline in woody cover without corresponding negative externalities such as decreases in grass cover or biodiversity. However, after three years, the woody community completely recoverd with a 23% increase in woody cover from the first to third year post-fire. The prescribed fire catchment saw minor decreases in woody plant dominance that rebounded quickly to pre-fire values. Our results suggest that reversing encroachment will likely require a long-term approach, along with applying a combination of pressures that reduce woody abundance and promote fuel loads to intensify fire.
Point cloud data from terrestrial laser scanning for stem volume modelling of Scots pine trees
<p>Stem volume is a key forest inventory attribute characterizing growth and yield of individual trees and forest stands. Three-dimensional information from terrestrial laser scanning (TLS) can be used to reconstruct tree stems and provide information on stem volume as well as stem shape. We collected diameter at breast height and height information with traditional field measurements as well as preprocessed TLS point cloud data on 230 Scots pine trees (<em>Pinus sylvestris L.</em>) from southern Finland. The data set here includes three-dimensional information on Scots pine tree stems derived from TLS point clouds. The usage of this data set can include, but is not limited to, development of point cloud processing algorithms for single tree stem reconstruction and investigations of of stem volume modelling for Scot pine. </p> <p>This data set includes two files: Scots_pines.txt includes DBH and height information based on field measurements from the 230 Scots pine trees. File includes the following columns: treeID, DBH, and h, where DBH is presented in cm and h (i.e. tree height) in m. Stem_points.zip, on the other hand, includes 230 laz-files where figure in the name of the laz-file refers to the tree ID in Scots_pines.txt-file. Laz-files include three columns that describe x, y, and z, coordinates (in meters) of stem points in a local coordinate system extracted from the normalized TLS point clouds (i.e. z coordinate describes height above ground).</p>
Characterization of a loss-offunction NSF attachment protein beta mutation in monozygotic triplets affected with epilepsy and autism using cortical neurons from proband-derived and CRISPR-corrected induced pluripotent stem cell lines
<p>RNA-seq data of matured cortical neurons (8-weeks old) derived from the induced pluripoent stem cells (iPSC) of control parents (CtrlF and CtrlM) and corrected proband. There are three replicates (Rep1, Rep2, Rep3) for each sample with Forwad read (R1_001.fastq.gz)</p> <p>CtrlF: Control Father sample</p> <p>CtrlM: Control mother sample</p> <p>NDD_01_Corr_Het: Heterozygous correction of NAPB mutation (c.354+2T>G) in NDD_01 proband</p> <p>NDD_05_Corr_Hom: Homozygous correction of NAPB mutation (c.354+2T>G) in NDD_05 proband</p>
Phase Object Reconstruction for 4D-STEM using Deep Learning, (4D-STEM Example Data)
<p><strong>Overview </strong></p> <p>This repository contains 2 example 4D-STEM datasets format from the paper <a href="https://arxiv.org/abs/2202.12611">"Phase Object Reconstruction for 4D-STEM using Deep Learning"</a>. The data was written to hdf5 for compatibility with the python programming language. When reading from these files consider possibly different storage conventions (Row major vs. column major format). Data may need to be transposed accordingly.</p> <p> </p> <p><strong>Parameters</strong></p> <p>The twisted bilayer graphene dataset is simulated. The smaller file is an experimental SrTiO<sub>3</sub> dataset.</p> <table> <thead> <tr> <th scope="row"> </th> <th scope="col">Graphene</th> <th scope="col">STO</th> </tr> </thead> <tbody> <tr> <th scope="row">E0</th> <td>200kV</td> <td>300kV</td> </tr> <tr> <th scope="row">Apeture</th> <td>25 mrad</td> <td>20 mrad</td> </tr> <tr> <th scope="row">Detector Size</th> <td>2.5 Å<sup>-1</sup></td> <td>1.6671 Å<sup>-1</sup></td> </tr> <tr> <th scope="row">Dimensions</th> <td>101x101x128x128</td> <td>60x60x64x64</td> </tr> <tr> <th scope="row">Step Size</th> <td>0.2</td> <td>0.1818</td> </tr> </tbody> </table> <p><br> </p>
Crowdsourcing vibration data stemming from different transportation usages
<p> </p> <p>Crowdsourcing vibration data stemming from different activities and transportation usages (by trains, by buses, by bicycles by walking). We present a comprehensive dataset that provides the pattern of five activities walking, cycling, taking a train, a bus or a taxi. The measurements are carried out by embedded sensor accelerometer in smartphones. The dataset offers dynamic responses of subjects carrying smartphones in varied styles as they performing the five activities through vibrations acquired by accelerometers. The dataset contains corresponding time stamps and vibrations in three directions longitudinal, horizontal, and vertical stored in an Excel Macro-enabled Workbook (xlsm) format can be used to train an AI model in a smartphone which has potentials to collect people’s vibration data and decides what movement is being conducted. Besides, with more data are received, the database can be updated and it can be fed to train the model with a larger dataset. The prevalent of the smartphone opens the door of crowdsensing which leads to the pattern of people talking public transports can be understood. Furthermore, the time consumed in each activity is available in the dataset. Therefore, with a better understanding of people using public transports, the service and schedule can be planned perceptively. Activities to obtain the dataset are jointly funded by H2020 and Hitachi Europe.</p>
Trellis-forming stems of a tropical liana Condylocarpon guianense (Apocynaceae): a plant-made safety net constructed by simple "start-stop" development
<p>Data supporting article describing mechanical and structural organisation of a climin g plant trellis system sin the tropical rainforest of French Guiana</p> <p>Tropical vines and lianas have evolved mechanisms to avoid mechanical damage during their climbing life histories. We explore the mechanical properties and stem development of a tropical climber that develops trellises in tropical rain forest canopies. We measured the young stems of <em>Condylocarpon guianensis</em> (Apocynaceae) that construct complex trellises via self-supporting shoots, attached stems and unattached pendulous stems. The results suggest that in this species there is a size (stem diameter) and developmental threshold at which plant shoots will make the developmental transition from stiff young shoots to later flexible stem properties. Shoots that do not find a support remain stiff, becoming pendulous and retaining numerous leaves. The formation of a second TYPE II (lianoid) wood is triggered by attachment, guaranteeing increased flexibility of light-structured shoots that transition from self-supporting searchers to inter-connected net-like trellis components. The results suggest that this species shows a “hard-wired” development that limits self-supporting growth among the slender stems that make up a liana trellis. The strategy is linked to a stem-twining climbing mode and promotes a rapid transition to flexible trellis elements in cluttered densely branched tropical forest habitats. These are situations that are prone to mechanical perturbation via wind action, tree falls and branch movements. The findings suggest that some twining lianas are mechanically fine-tuned to produce trellises in specific habitats. Trellis building is carried out by young shoots that can perform very different functions via subtle development changes in order to ensure a safe space occupation of the liana canopy.</p>
Water Dawgs STEM Confidence Survey Results, 2023
This dataset originates from a STEM confidence survey conducted during the Water Dawgs program—a paid summer initiative hosted at the University of Georgia (UGA) in Athens, Georgia, USA. Held over 10 days in Summer 2023, the program engaged 16 high school students in a hands-on experience in freshwater science. Water Dawgs was designed to support students’ academic and professional development, with an emphasis on increasing access for individuals from populations historically excluded from STEM fields. The initiative was part of the broader impacts of two National Science Foundation-funded research projects and was shaped by three main objectives: (1) to expand access to university-led STEM opportunities by collaborating with a local public high school to recruit students from underrepresented backgrounds; (2) to highlight the connections between environmental science and students’ everyday lives and future career options, including non-STEM pathways; and (3) to foster greater self-efficacy in engaging with STEM subjects, particularly environmental science. The survey was administered at both the beginning and conclusion of the 10-day program to assess changes in participants’ confidence related to STEM. The survey measured STEM confidence using a Likert scale ranging from 1 to 5, with 1 indicating "not at all confident" and 5 indicating "totally confident." The included R code contains a script to generate a figure and summary statistics for questions related to general STEM confidence, specifically Questions 2, 6, 7, 9, and 12. One participant who only submitted a post-program survey was excluded from the dataset and analysis to ensure consistency across responses.
Aspen Forest Stem Map and Tree Census at the University of Michigan Biological Station, Pellston, MI 1974-2018
In 1974, a one hectare plot was established at the University of Michigan Biological Station to further understand successional trajectories of birch and aspen forests in northern Michigan. Trees with a DBH greater than 5 cm were inventoried and later, the location of the tree within the plot was documented by the UMBS resident biologist. Plots were remeasured 5 additional times by different groups at the station.
Stem maps of eight 1 ha forest plots distributed around Ann Arbor, MI and around the University of Michigan Biological Station (UMBS)
In this project we established a network of forest inventory plots to gather the data needed to forecast future forest performance under global change. Data collected from forest inventory plots, i.e., size and location of individual trees from all ages and species, have been shown to be particularly useful to link tree species demographic rates (survival, growth, age at maturity, fecundity) with community characteristics (assemblages and species turnovers), and are also widely used to estimate biomass removal (logging) and biomass production (carbon sequestration).
Effects of long-term nitrogen addition on Solidago altissima stem morphology, size, and herbivory at Kellogg Biological Station 2016-2022
We surveyed naturally occurring tall goldenrod (Solidago altissima) plants in a long-term nitrogen addition field experiment at the Kellogg Biological Station's T7 untilled succession plots in the Main Cropping System Experiment (https://lter.kbs.msu.edu/research/long-term-experiments/main-cropping-system-experiment/). We collected data on the defensive stem nodding morph (which helps plants evade apex-galling herbivores) and presence of galls in 2016, 2021, and 2022.
SDR01 Intra-clonal stem demography of Cornus drummondii in response to fire and browsing at Konza Prairie
Intra-clonal stem density, natality, mortality, flowering and relative growth rate within discrete Cornus drummondii shrubs in response to fire frequency (4- vs 20-yr burn intervals) and simulated browsing. Tagged stems within individual shrubs were tracked and measured at the beginning and end of each growing season in 2018 and 2019 to assess the interactions of fire and browsing on stem demography.
Detailed point cloud data on stem size and shape of Scots pine trees
<p>This data set is comprised of three packed zip files and they include text files of 3D information from terrestrial laser scanning (TLS) and aerial imagery from unmanned aerial vehicle (UAV) from individual Scots pine trees within 27 sample plots from three test sites located in southern Finland.</p> <p>TLS data acquisition was carried out with Trimble TX5 3D laser scanner (Trible Navigation Limited, USA) for all three study sites between September and October 2018. Eight scans were placed to each sample plot and scan resolution of point distance approximately 6.3 mm at 10-m distance was used. Artificial constant sized spheres (i.e. diameter of 198 mm) were placed around sample plots and used as reference objects for registering the eight scans onto a single, aligned coordinate system. The registration was carried out with FARO Scene software (version 2018). Aerial images were obtained by using an UAV with Gryphon Dynamics quadcopter frame. Two Sony A7R II digital cameras were mounted on the UAV in +15° and -15° angles. Images were acquired in every two seconds and image locations were recorded for each image. The flights were carried out on October 2, 2018. For each study site, eight ground control points (GCPs) were placed and measured. Flying height of 140 m and a flying speed of 5 m/s was selected for all the flights, resulting in 1.6 cm ground sampling distance. Total of 639, 614 and 663 images were captured for study site 1, 2, and 3, respectively, resulting in 93% and 75% forward and side overlaps, respectively. Photogrammetric processing of aerial images was carried out following the workflow as presented in Viljanen et al. (2018). The processing produced photogrammetric point clouds for each study site with point density of 804 points/m<sup>2</sup>, 976 points/m<sup>2</sup>, and 1030 points/m<sup>2</sup> for study site 1, 2, and 3, respectively.</p> <p>The sample plots within the three test sites have been managed with different thinning treatments in either 2005 or 2006. The experimental design of the sample plots includes two levels of thinning intensity and three thinning types resulting in six different thinning treatments, namely i) moderate thinning from below, ii) moderate thinning from above, iii) moderate systematic thinning, iv) intensive thinning from below, v) intensive thinning from above, and vi) intensive systematic thinning, as well as a control plot where no thinning has been carried out since the establishment. More information about the study sites and samples plots as well as the thinning treatments can be found in Saarinen et al. (2020a).</p> <p>The data set includes stem points of individual Scot pine trees extracted from the point clouds. More about the method of extraction can be found in Saarinen et al. (2020a, 2020b) and Yrttimaa et al. (2020). The title of the zip file refers to the study sites 1, 2, and 3. The title of the text files includes the information on the test site, the plot within the test site, and the tree within the plot. The text files contain stem points extracted from the TLS point clouds. The columns “x” and “y” contain x- and y-coordinates in a local coordinate system (in meters), in column “h” is the height of each point in meters above ground, and treeID is the tree identification number. The columns are separated by space.</p> <p>Based on the study site and plot number, files from different thinning treatments can be identified by using the information in Table 1 in Saarinen et al. (2020b).</p> <p> </p> <p><strong>References</strong></p> <p>Saarinen, N., Kankare, V., Yrttimaa, T., Viljanen, N., Honkavaara, E., Holopainen, M., Hyyppä, J., Huuskonen, S., Hynynen, J., Vastaranta, M. 2020a. Assessing the effects of stand dynamics on stem growth allocation of individual Scots pines. bioRxiv 2020.03.02.972521. <a href="https://doi.org/10.1101/2020.03.02.972521">https://doi.org/10.1101/2020.03.02.972521</a></p> <p>Saarinen, N., Kankare, V., Yrttimaa, T., Viljanen, N., Honkavaara, E., Holopainen, M., Hyyppä, J., Huuskonen, S., Hynynen, J., Vastaranta, M. 2020b. Detailed point cloud data on stem size and shape of Scots pine trees. bioRxiv 2020.03.09.983973. <a href="https://doi.org/10.1101/2020.03.09.983973">https://doi.org/10.1101/2020.03.09.983973</a></p> <p>Viljanen, N., Honkavaara, E., Näsi, R., Hakala, T., Niemeläinen, O., Kaivosoja, J. 2018. A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone. Agriculture 8: 70. <a href="https://doi.org/10.3390/agriculture8050070">https://doi.org/10.3390/agriculture8050070</a></p> <p>Yrttimaa, T., Saarinen, N., Kankare, V., Hynynen, J., Huuskonen, S., Holopainen, M., Hyyppä, J., Vastaranta, M. 2020. Performance of terrestrial laser scanning to characterize managed Scots pine (<em>Pinus sylvestris</em> L.) stands is dependent on forest structural variation. EarthArXiv. March 5. <a href="https://doi.org/10.31223/osf.io/ybs7c">https://doi.org/10.31223/osf.io/ybs7c</a></p>
In situ FTIR, EXAFS and HR-STEM data for Pd/TiO2 samples under red-ox conditions
<p>Files Pd_photo-oxidation.xmu.dat and Pd_dep-oxidation.xmu.dat contain the sequence of X-ray absorption spectra during starting from the pre-reduced state (after reduction in H2) during heating in O2 from 50 to 400 for Pd_photo and Pd_dep samples, respectively (synthesized using photodeposition and deposition-precipitation methods). The last two columns in each file correspond to the as-synthesized state of the corresponding sample (before reduction in hydrogen) and reference palladium foil. </p> <p>Pd_photo.ftir.dat and Pd_dep.ftir.dat contain the sequence of the FTIR spectra for the same samples taken at room temperature after sending 35 mbar of CO on pre-oxidized samples.</p> <p>Video files show the evolution of the structure of Pd_dep and Pd_photo samples sample under different atmospheres and temperatures, visualized by in situ HR-STEM microscope.</p>
Dataset for a publication: "PLLA honeycombs activated by plasma and high energy excimer laser for stem cell support"
<p>The dataset accompanies the article <em>"PLLA Honeycombs Activated by Plasma and High-Energy Excimer Laser for Stem Cell Support."</em> It is organized into several subfolders, each corresponding to a different analytical method used in the study, with data presented in the manuscript. The main folder is structured as follows:</p> <ol> <li><strong>AFM</strong></li> <li><strong>Contact Angle</strong></li> <li><strong>Zeta Potential</strong></li> <li><strong>SEM</strong></li> <li><strong>EDS</strong></li> <li><strong>XPS</strong></li> <li><strong>Cytocompatibility</strong></li> </ol> <p>Each subfolder contains the relevant data associated with the specific analysis.</p> <p> </p> <p>For more details, please read the <strong>README - Description of data and analysis informations_PS.txt</strong> file.</p> <p> </p> <p><strong> </strong></p> <p><strong>Dataset versions:</strong></p> <p>There are no newer versions so far.</p>
Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort
<p># Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort" - Rev #1</p> <p>This is the dataset for the paper titled "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort".</p> <p>In case of questions, feel free to contact the authors, *anonymised*, ORCID: https://orcid.org/*anonymised*, current affiliation and email: *anonymised*</p> <p>## Survey 2019 ##<br> The raw survey data for the initial 2019 survey is available in the file *survey2019_anon.csv*. Note that the data is anonymised as free-text comments have been removed. Explanations on the variables and their levels are given in the files *variables_survey2019.csv* and *values_survey2019.csv*.<br> The questionnaire for the 2019 survey is contained in *survey2019_instrument.pdf*.</p> <p>## Survey 2020 ##<br> The raw survey data for the 2020 survey is available in the file *rdata_anon_survey2020.csv*. Additional scripts are supplied to reproduce the exploratory factor analysis. The main entry is the file *EFA.R*, which imports the data. The file contains some comments on the process.<br> The questionnaire for the 2020 survey is contained in *survey2020_instrument.pdf*.</p> <p>## Interviews ##<br> The interview guide used for the five interviews is available in the file *interview_instrument.pdf*.</p>
Raw data: Diversity in root architecture of durum wheat at stem elongation under drought stress
<p>Raw data on above and below ground traits from a greenhouse drought stress experiment with six durum wheat varieties performed at Tuscia University, Viterbo, Italy. Measurements were performed at stem elongation stage; recorded traits: plant shoot length, dry weight, number of leaves and tillers; total root length, root surface area, mean diameter, volume, number of tips, forks, crossings, root dry weight and root angle. Root measurments were performed on the whole root system and the topsoil area (upper 5 cm). </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.