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36 results for “NC data”
Supplementary data (CC BY-NC-SA 4.0): A reactive neural network framework for water-loaded acidic zeolites
<p><strong>Content (Creative Commons Attribution Non Commercial Share Alike 4.0 International):</strong></p><p>This dataset provides supplementary data to "A reactive neural network framework for water-loaded acidic zeolites". It contains trained Neural Network Potentials (NNP and ΔNNP model), scripts, and all energy and force data used in this work at the (Δ)NNP, ReaxFF, and DFT (SCAN+D3(BJ) and ωB97X-D3(BJ)) level. Energy and forces are stored as ASE trajectory files (traj), readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE). In addition, this repository contains the generated training database with DFT (SCAN+D3(BJ)) energies and forces as SchNetPack1.0 database (SiAlOH.db) file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>.</p><ol><li>"aimd_simulations.zip" - VASP INCAR file, XDATCAR and traj file for 10 ps AIMD run (Supplementary Figure 6) and NNP level (re-)calculated energies/forces ("aimd_nnp_recalc.traj")</li><li>"biased_dynamics.zip" - VASP/Plumed input and output files for DFT (SCAN+D3(BJ)) and NNP level biased dynamics including traj files (Supplementary Figure 12)</li><li>"database_input.zip" - structure (cif) files of the initial structures used for database generation (Supplementary Table 1)</li><li>"delta_nnp.zip" - (pytorch) ΔNNP model (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>) together with example scripts </li><li>"error_stats.zip" - traj files of all generalization tests (Figure 1 and Supplementary Figure 4) storing energies/forces at the SCAN+D3(BJ), ReaxFF, and NNP level as well as traj files with ΔNNP and ωB97X-D3(BJ) energies/forces for a subset taken from biased dynamics runs (Supplementary Figure 11)</li><li>"md_simulations.zip" - NNP level MD trajectories of all generalization test (Figure 1 and Supplementary Figure 4) runs including an example script for an MD run</li><li>"neb_calculations.zip" - traj files and example scripts for NEB calculations at the (Δ)NNP along with the corresponding DFT energy/force data (SCAN+D3(BJ) and ωB97X-D3(BJ))</li><li>"nnps.zip" - (pytorch) NNP model files (compatible with <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a>)</li><li>"silica_database.zip" - output files of the single-point (SP) and optimization test runs (Supplementary Figure 1) of pure silica structures together with an example structure optimization script </li><li>"SiAlOH.db" - DFT (SCAN+D3(BJ)) training database as SchNetPack1.0 database file readable by ASE and <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li></ol>
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC, USA, 2022-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 01, Highlands Biological Station, Highlands, NC
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Betula alleghanensis and formerly Tsuga canadensis, the latter of which has mostly succombed to the Hemlock Woolly Adelgid.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 02, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in a remnant old-growth Canada Hemlock Forest (typic subtype) community dominated by an understory of Rhododendron maximum and an overstory of Tsuga canadensis, the majority of which are still alive and have been treated with systemic insecticides to protect against infestations of the Hemlock Woolly Adelgid. Other trees include Betula alleghanensis, Acer rubrum, and Quercus rubra. The pressure transducer is located in the thalweg of Coker Creek, a second order stream that flows into Lindenwood Lake.
Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
Daily Summary of Soil moisture, soil temperature, air temperature, stream water temperature, stream stage and discharge data from Soil Moisture Station 03, Highlands Biological Station, Highlands, NC, 2021-2025
Measurements of soil moisture, soil temperature, air temperature, stream temperatue, and stream stage/discharge were collected as part of a long-term monitoring project at the Highlands Biological Station, Western Carolina University, Highlands, North Carolina. The sensor station is located in an acidic cove forest (high elevation subtype) dominated by an understory of Rhododendron maximum and an overstory of Liriodendron tulipifera, Betula alleghanensis, and Tsuga canadensis, the latter of which has several trees that have succombed to the Hemlock Woolly Adelgid, though living trees have been treated with a systemic insecticide. The pressure transducer is located in a second order stream known as Station Branch.
Fish and crayfish density and count data for Peeks Creek, Macon County, NC, USA 2005-2014, 2019, and 2022 following a catastrophic debris flow, as well as six reference streams
We followed the process of recovery of the fish and crayfish assemblage in Peeks Creek, a high-gradient second order stream in the Little Tennessee River watershed of North Carolina, after a debris flow devastated the channel and its riparian zone. After 15 years, the fish assemblage had recovered, and the channel and riparian zone had stabilized. Of the three major components of the fish assemblage, Rainbow Trout (Oncorhynchus mykiss (Walbaum)), a strong swimmer, reappeared in year 1. Longnose Dace (Rhinichthys cataractae (Valenciennes in Cuvier and Valenciennes)) reappeared in year 3. Mottled Sculpin (Cottus bairdii Girard), a weak swimmer, did not become established until year 6 and only resumed expected abundance in year 9. Appalachian Brook Crayfish (Cambarus bartonii cavatus Hay) numbers recovered quickly, though only one individual was found the year following the debris flow. Unassisted natural recovery occurred after a costly engineered restoration project had been rejected and arguably represents the preferable solution. However, recovery of the fish assemblage may not have been achieved if the stream flowed directly into an impoundment or low gradient river that lacked the source of species for recolonization, or if the stream had been located above a barrier to upstream movement.
NC Community College President Data Set
<p>NCCCPDS. A working data set of presidents serving in North Carolina community colleges from the mid-1960s. Includes name, year, college, gender identity, degree, degree university, and field. Data were retrieved from publicly available documents including course catalogs, newspapers, obituaries, and university alumni records.</p>
Detecting coarse beach sediment using remotely sensed imagery at the FRF, Duck, NC, USA: Labeled images, deep learning model, testing data, and predictions.
<p>This data record contains 5 zip files all used to build and use a semantic segmentation model to operate on beach imagery taken at the Field Research Facility (FRF) in Duck, North Carolina, USA. All data is from 2015-2021</p> <p>The `training_data.zip` contains all data used to train the ML model. All images come from the north facing (c1) camera. This zip file includes: a list of classes used to label the imagery, and folders of 107 images, 107 sparse annotations (doodles), 107 labels, and 107 overlays. All labeling was done with the open-source labeling tool ‘Doodler (Buscombe et al., 2021).</p> <p>The `model.zip` file contains the ML model, and associated metadata. This includes: a JSON model configuration file, a figure showing model training statistics, an `.npz` file of model training output, a list of training and validation files, the model as an h5 file and in the Tensorflow ‘saved model’ format. All modeling was done with Segmentation Gym (Buscombe & Goldstein 2022).</p> <p>The `test_data_c6.zip` file contains all data from the south facing (c6) camera to test the ML model. This includes: a list of classes used to label the imagery, and folders of 10 images, 10 sparse annotations (doodles), 10 labels, and 10 overlays. All labeling was done with the open-source labeling tool ‘Doodler (Buscombe et al., 2021). Testing the model with this data was done with codes in: https://github.com/ebgoldstein/FRF_GrainSize</p> <p>The `test_data_c1.zip` file contains all data from the north facing (c1) camera to test the ML model. This includes: a list of classes used to label the imagery, and folders of 10 images, 10 sparse annotations (doodles), 10 labels, and 10 overlays. All labeling was done with an open-source labeling tool ‘Doodler (Buscombe et al., 2021). Testing the model with this data was done with codes in: https://github.com/ebgoldstein/FRF_GrainSize</p> <p>The `predictions.zip` file contains 4418 images from the north facing (c1) camera that were run through the trained segmentation model as well as the resulting output (presented as side-by-side image and overlays). These images were created using codes in Segmentation Gym (Buscombe & Goldstein 2022).</p>
Macon County, NC Middle School Climate Data
The climate station at the Macon Middle School near Franklin, NC was established in February 2000. The objectives were to: 1) locate a climate station outside of the Coweeta Basin, but within Macon County, North Carolina, measuring air temperature, air humidity, precipitation, solar radiation, wind speed, wind direction, vapor pressure, and barometric pressure 2) provide students and teachers at the school with a unique teaching tool, and 3) provide the public with an online archive of weather data.
Microclimate data from stations within the Great Smoky Mountains National Park, NC
This dataset contains measurements of air temperature, relative humidity, soil temperature, soil bulk electrical conductivity, and soil volumetric water content from a sites located in the Great Smoky Mountains National Park, NC. Soil temperature, soil bulk electrical conductivity, and soil volumetric water are measured at 0-30cm and 30-60cm below ground surface at locations 25 meters above gradient and 25 meters below gradient of a central transect location where air temperature and relative humidity are measured at 1.5 meters above ground surface. Measurements are taken every 60 seconds with average, minimum, and maximum values saved hourly to the output table.
US National Native Bee Monitoring RCN Data Management Workshop: CC BY NC Videos
<p>The US National Native Bee Monitoring Research Coordination Network (RCN) held a two-day workshop on data management best practices for native bee inventory, survey, and monitoring data on March 28 and 30, 2023. Videos in this data set were played at the workshop. These videos are released with a CC BY-NC license. These videos are for non-commercial use only. Please cite the presenter(s) of the video(s) you use. This data set includes the following videos: </p><ul><li>APHIS National Honey Bee Pests and Diseases Survey by Anne LeBrun</li><li>Importance of FAIR in Biodiversity Science and Research by Elizabeth R. Ellwood</li><li>Bugflow: A Community Driven Repository for Entomology Digitization Resources by Crystal Maier</li><li>A Primer on iNaturalist Bee Data by Keng-Lou James Hung, Paige Chesshire, Michael Orr, Alice Hughes, Jess Mullins, Katherine Parys, Patricia Simpson, Lindsie McCabe, Neil Cobb, and John Ascher</li></ul>
Tree census, demography, and exposed canopy area data at the Coweeta LTER Terrestrial Gradient Sites, Coweeta Hydrological Laboratory, Otto, NC from 1993 to 2016
The five Terrestrial Gradient sites were established in the early 1990s as part of the 1990 Coweeta LTER Renewal. The original terrestrial gradient sites were 20 x 40-m. In the late 1990s the plots were expanded to 80 x 80-m and later (around 1998) they were slope-corrected by Clark's lab using survey equipment. Much of the Coweeta LTER “core” datasets have been collected from the gradient plots. This study is one of the long-term studies that are ongoing with defined sampling intervals. The tree demography and census study consists of trees census every two years and seeds collected ~5 x each year.
Intensive Stream Survey Geomorphology Data from 2010 to 2011 at the Coweeta Hydrologic Laboratory, Otto, NC
From June 2010 until February 2011, fifty streams were surveyed to determine the physical characteristics of streams in forested, traditional land use, and developed settings. Cross-sectional measurements were taken at 16 cross-sections on each reach. The distance between each cross-section was twice the average active channel width (which was determined prior to the survey). At one to three locations within each surveyed reach, slope was determined by placing a laser level at a location upstream and then measuring the amount of elevation change at the water surface. Between each cross-section, the instream habitat was recorded. Large woody debris was measured where it was found within the surveyed reach of the stream. Only LWD with diameter >10 cm was measured. At a representative riffle within the reach, a Wolman pebble count (100 randomly selected pieces of sediment) was taken.
GIS vector data for sample locations and plots associated with the Hillslope Study in Macon County, NC
The Hillslope Study sites represent a gradient of landscapes, including forested, valley agriculture, and mountain housing developments. These locations and plots were used to collect samples of various matrices for numerous analyses at differing intervals. The data set consists of Open Office spreadsheet and other files that document all the Hillslope Study locations.
Aeolian Saltation Data at Duck, NC - 8 Nov 2021
<p>Aeolian saltation data collected on the north property of the Field Research Facility (FRF) in Duck, NC associated with the passing of a Nor'Easter system. Time series data includes 1Hz measurements from a Sensit H14-LIN sensor, 1 Hz wind measurements from a horizontally mounted ZX TM doppler wind lidar sensor, and tidal measurements made from the end of the FRF pier. These time series data are provided as CSV files individually for each sensor, with headers of the CSV files indicating the variables of interest. Addititionally, a Sequoia LISST-Holo2 sensor was deployed to measure properties of the aeolian saltation layer at 10Hz. Particle grain size information exported from the HoloBatch program is additionally provided, with the raw reconstructed particle height relative to the sensor lens provided. More details regarding these measurements can be found in the following manuscript:</p> <p>Cohn, Dickhudt, and Marshall (2022). In-situ measurement of grain size characteristics within the aeolian saltation layer on a coastal beach. Earth Surface Processes and Landforms</p>
WorldCereal open global harmonized reference data repository (CC-BY-NC licensed data sets)
<p>Within the <strong>ESA funded</strong> WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets.</p> <p>This publication includes those harmonized data sets of which the original data set was published under the CC-BY-NC license or a license similar to CC-BY-NC. See document "_In-situ-data-World-Cereal - license - CC-BY-NC.pdf" for an overview of the original data sets. Currently this publication only includes a few small data sets for Tanzania originating from a disease monitoring program of the International Maize and Wheat Improvement Center (CIMMYT). CIMMYT made more data available for countries like Kenya, Ethiopia, Rwanda and, Malawi. However due project contraints these data sets were not yet harmonized.</p>
Monthly data from Climate Station 1 (CS01), Coweeta Hydrologic Laboratory, Otto, NC, 1934-2018
This dataset contains base-line climatic information for the main climate station (CS01) at Coweeta Hydrologic Laboratory in Macon County, North Carolina, USA. The station is operated by the Southern Research Station, Forest Service, USDA. CS01 is also a cooperative station with the National Weather Service. Since May 1963 it has been located in a grassy field NW of the junction of Ball Creek and Shope Fork of Coweeta Creek. Previously CS01 was located about 100m SW of its current location. The current elevation is 685.5m (2249ft) at latitude 35-3-37.21N and longitude 83-25-49.02W. During the 1940s, forest re-growth was tolerated up to 150 feet from the station. In August 1949, the larger opening was reestablished. The high elevation precipitation gage is located in a forest opening on Mooney Gap at elevation 1362.6m (4475ft). Additional USDA Forest Service Data for this climate station can be found at this link: http://www.srs.fs.usda.gov/coweeta/tools-and-data/
Supplementary data (CC BY-NC-SA 4.0): Migration of Zeolite-Encapsulated Subnanometre Platinum Clusters via Reactive Neural Network Potentials
<p><strong>Content (Creative Commons Attribution Non Commercial Share Alike 4.0 International):</strong></p> <ul> <li>Trajectory files containing structures, energies and forces of CHA, MWW (including MWW*), TON, MFI (Pt1, Pt3, Pt5 at 750, 1000, 1250 K) as (extended) xyz files readable by the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment </a>(ASE)</li> <li>Animated gif files of Pt1 migration between double-six rings in CHA, Pt3 jump through an eight-ring in CHA, and insertion of Pt1 into a t-pen unit in MFI</li> <li>Neural Network Potential (NNP) files readable by <a href="https://github.com/atomistic-machine-learning/schnetpack/tree/schnetpack1.0">SchNetPack version 1.0</a></li> </ul>
ScienceDex guides
Understand access before you commit
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.