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321 results for “Walnut”
Urban Riparian Wetland Hydrology Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA
<p>This is the initial release of a <strong>hydrology</strong> dataset pertaining to the <strong>riparian floodplain wetlands</strong> alongside Walnut Creek in Raleigh, North Carolina USA. Walnut Creek is the main drainage channel in an <strong>urbanized watershed</strong> (HUC-12: 030202011101) in central North Carolina. There are several riparian floodplain wetlands along the creek which are largely supplied by <strong>urban stormwater</strong> runoff including directed <strong>storm sewer flows</strong> and regular <strong>overbank flooding</strong> events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of <strong>North American beavers (<em>Castor canadensis</em>)</strong>. This dataset contains data specific to the hydrology of Walnut Creek, and the surface ponds and groundwater at the <strong>Walnut Creek Wetland Park</strong> which is actively influenced by resident beavers. The period of this dataset is from <strong>January 22, 2023 through January 30, 2024</strong>. </p> <p>The core of the dataset is water stage measured in five surface pond sites and six groundwater monitoring wells within Walnut Creek Wetland Park. This data was collected using synchronized Solinst Levelogger pressure transducer sensors at 15-minute intervals, compensated with corrections for barometric pressure measured locally using a Solinst Barologger sensor. In addition to this data collected by the authors, this dataset also includes publicly available stream stage and precipitation data obtained from the <strong>US Geological Survey,</strong> and weather and soils data from the <strong>North Carolina State Climate Office</strong>. In total, this dataset aims to provide a comprehensive view of surface and subsurface hydrology in the studied wetlands as it connects with precipitation events, antecedent moisture conditions, directed stormwater flows and overbank flood events. </p> <p>This hydrology dataset is intended to accompany the <u>separate</u> <strong>water quality dataset</strong> published on Zenodo at URL: <a href="https://doi.org/10.5281/zenodo.10888463">https://doi.org/10.5281/zenodo.10888463</a>. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont.</p> <p>This dataset resulted from research supported with a Graduate Student Research Grant awarded by the <strong>North Carolina Water Resources Research Institute (WRRI)</strong>, under Project Number 23-10-W: "Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds". </p> <p>This material is based upon work supported by the <strong>National Science Foundation (NSF)</strong> Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.</p> <p>Special thanks to <strong>Raleigh Parks</strong> and <strong>Walnut Creek Wetland Park</strong> for making this work possible.</p>
Cone-Beam Computed Tomography Dataset of a Walnut
<p><strong>Summary</strong></p> <p>This dataset is a collection of X-ray projection images of a walnut imaged in a cone-beam computed tomography (CBCT) scanner. The dataset also includes a metadata file, specifying the scan geometry and other important scan parameters.</p> <p> </p> <p><strong>Description</strong></p> <p><em>Sample Information</em></p> <p>The sample is a walnut in its shell. For the scanning process double-sided tape was used to attach the sample to a plastic tube placed into the rotation stage.</p> <p><em>Scanner</em></p> <p>The measurements were acquired using a cone-beam computed tomography scanner designed and constructed in-house in the Industrial Mathematics Computed Tomography Laboratory at the University of Helsinki. The scanner consists of a molybdenum target X-ray tube (Oxford Instruments XTF5011), a motorized rotation stage (Thorlabs CR1-Z7), and a 12-bit, 2240x2368 pixel, energy-integrating flat panel detector (Hamatsu Photonics C7942CA-22).</p> <p><em>Scan Settings</em></p> <p>721 X-ray projections were acquired using an angle increment of 0.5 degrees. The X-ray source voltage and tube current were set at 40 kV and 1 mA, respectively. The exposure time of the flat panel detector was set to 1000 ms.</p> <p><em>Data Post-Processing</em></p> <p>Two correction images were acquired before scanning the sample. A dark current image was created by averaging 100 images taken with the X-ray source off. A flat-field image was created by averaging 100 images taken with the X-ray source switched on with no sample placed in the scanner. After the scan, dark current and flat-field corrections were applied to each projection image using the Hamamatsu HiPic imaging software version 9.3.</p> <p><em>Data Format</em></p> <p>The X-ray projections are stored in .tif format. The metadata is contained in .txt file with formatting that is both human-readable and machine-readable.</p> <p><em>Notes</em></p> <p>Due to a slightly misaligned center of rotation in the scanner, the CT reconstructions can appear blurry. It was empirically observed that this problem can be compensated for quite well by shifting each projection left by 5 pixels, using circular boundary conditions, before performing any other operations on the projections.</p> <p> </p> <p><strong>Research Group</strong></p> <p>This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland: <a href="https://www2.helsinki.fi/en/researchgroups/inverse-problems">https://www2.helsinki.fi/en/researchgroups/inverse-problems</a>.</p> <p> </p> <p><strong>Additional Links</strong></p> <p>This dataset was originally created as part of a tutorial on working with measured X-ray data in computed tomography. A video tutorial on the measurement process can be found on the Inverse Problems Channel on YouTube at <a href="https://www.youtube.com/watch?v=CWUomAmUDys">https://www.youtube.com/watch?v=CWUomAmUDys</a>.</p> <p>To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected in the Industrial Mathematics Computed Tomography Laboratory, and available at <a href="https://github.com/Diagonalizable/HelTomo">https://github.com/Diagonalizable/HelTomo</a>.</p> <p>Please note that this is a an entirely separate dataset from the Walnut dataset accessible at <a href="https://zenodo.org/record/1254206">https://zenodo.org/record/1254206</a>, although both datasets have been created by the same research group.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.</p>
The GIS database of Woodnat project for the inventory and monitoring of walnut plantation in Italy and Spain
<p>The database contains 95 selected walnut plantations monitored with the financings of the H2020 WOODnat project in Italy and Spain and georeferenced in WGS84 reference system (EPSG 4326). For each plantation, stationary, cultural and climatic data are available; on a sample of 30 trees for each plot data of growth, wood quality and sanitary conditions are available. These data can be exploited to assess potential wood volume obtainable and quality of raw material, and to identify the weaknesses and errors, strengths and opportunities of the experiences conducted to plan future plantings with greater awareness.</p>
Urban Riparian Wetland Water Quality Dataset_Stormwater Capture in Beaver-mediated Wetlands along Walnut Creek, Raleigh, North Carolina, USA
<p><span>This is the initial release of a </span><strong><span>water quality</span></strong><span> dataset pertaining to the <strong>riparian floodplain wetlands</strong> alongside Walnut Creek in Raleigh, North Carolina USA. Walnut Creek is the main drainage channel in an <strong>urbanized watershed</strong> (HUC-12: 030202011101) in central North Carolina. There are several riparian floodplain wetlands along the creek which are largely supplied by <strong>urban stormwater</strong> runoff including directed <strong>storm sewer flows</strong> and regular <strong>overbank flooding</strong> events. In many of these wetlands local water retention and residence time in the surface ponds is mediated by the damming activity of <strong>North American beavers (</strong><em><strong>Castor canadensis</strong></em><strong>)</strong>. This dataset contains data specific to the water quality values of <strong>Walnut Creek</strong>, its tributary <strong>Little Rock Creek</strong>, and the surface ponds and groundwater at the <strong>Walnut Creek Wetland Park</strong> which is actively influenced by resident beavers. The period of this dataset is from <strong>January </strong></span><strong><span>5</span><span>, 2023 through </span></strong><strong><span>October 28</span><span>, 2023</span></strong><span>. </span></p> <p><span>This dataset includes a variety of common <strong>water quality parameters</strong> measured in situ by use of a <strong>YSI Pro water quality meter</strong>, as well as <strong>dissolved nutrient values</strong> determined by <strong>laboratory analysis</strong> of collected water samples.<span> </span>YSI data was collected on a <strong>weekly</strong> basis and water samples were collected for laboratory analysis on a <strong>monthly</strong> basis. Additional measurements and collection took place during <strong>six large rainfall events</strong> to allow comparison between baseflow and stormflow conditions across the site.<span> </span>This dataset aims to provide a comprehensive look at the water quality of Walnut Creek in comparison with the surface ponds and groundwater in the Walnut Creek Wetland Park, which are all ultimately sourced from <strong>urban stormwater runoff</strong>. </span></p> <p><span>This water quality dataset is intended to accompany the <u>separate</u> <strong>hydrology dataset</strong> published on Zenodo at URL: <a href="https://doi.org/10.5281/zenodo.10709630">https://doi.org/10.5281/zenodo.10709630</a>. Together, these datasets are meant to support an improved understanding of the water availability and water quality found in connection with beaver-mediated stormwater capture in an urbanized watershed in the North Carolina Piedmont.</span></p> <p><span> </span><span>This dataset resulted from research supported with a Graduate Student Research Grant awarded by the <strong>North Carolina Water Resources Research Institute (WRRI)</strong>, under Project Number 23-10-W: "Stormwater Diversion, Storage, and Treatment by Beaver-enhanced Floodplain Wetlands in Piedmont Urban Watersheds". </span></p> <p><span>This material is based upon work supported by the <strong>National Science Foundation (NSF)</strong> Graduate Research Fellowship Program (GRFP) under Grant No. (DGE 2137100). Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.</span></p> <p><span>Special thanks to <strong>Raleigh Parks</strong> and <strong>Walnut Creek Wetland Park</strong> for making this work possible.</span></p> <p><span>Laboratory analysis support for evaluation of dissolved nutrients (nitrate+nitrite, TKN, total phosphorus, and total organic carbon) was provided by the <strong>NC State Environmental and Agricultural Testing Services (EATS)</strong> laboratory, Department of Crop and Soil Sciences.</span></p> <p><span> </span><span>Additional laboratory analysis support for evaluation of dissolved nutrients (TKN and total phosphorus) was provided by the <strong>NC State Environmental Analysis Laboratory (EAL)</strong>, Department of Biological and Agricultural Engineering (BAE).</span></p> <p><span> </span><span>Usage of and technical support for the YSI Pro water quality meter used in this study was made possible by the <strong>Osburn Lab</strong>, Department of Marine, Earth and Atmospheric Sciences (MEAS), NC State University.</span></p>
X-ray computed tomography dataset of a walnut
<p>walnut_scan:</p> <ul> <li>scan performed with a conventional micro-CT</li> <li>1601 acquired projections as tiff stack</li> <li>info file containing corresponding metadata</li> </ul> <p> </p> <p>walnut_rec:</p> <ul> <li>reconstructed volume as tiff stack</li> <li>info file containing corresponding metadata</li> <li>reconstruction performed with pyXIT (see reference)</li> </ul> <p> </p>
Cone-Beam Computed Tomography Dataset of a Walnut Imaged at 4 Different Dose Levels
<p><strong>Summary</strong></p> <p>This dataset is a collection of X-ray projection images of a walnut imaged in a cone-beam computed tomography (CBCT) scanner, using four different dose levels. The dataset also includes a metadata file for each of the scans, specifying the scan geometry and other important scan parameters.</p> <p> </p> <p><strong>Description</strong></p> <p><em>Sample Information</em></p> <p>The sample is a walnut in its shell. For the scanning process double-sided tape was used to attach the sample to a plastic tube placed into the rotation stage.</p> <p><em>Scanner</em></p> <p>The measurements were acquired using a cone-beam computed tomography scanner designed and constructed in-house in the Industrial Mathematics Computed Tomography Laboratory at the University of Helsinki. The scanner consists of a molybdenum target X-ray tube (Oxford Instruments XTF5011), a motorized rotation stage (Thorlabs CR1-Z7), and a 12-bit, 2240x2368 pixel, energy-integrating flat panel detector (Hamatsu Photonics C7942CA-22).</p> <p><em>Scan Settings</em></p> <p>The dataset consists of four different scans of the same sample. For each scan 360 X-ray projections were acquired using an angle increment of 1 degrees, with one additional frame taken at the end to estimate sample movement. The X-ray source was set at 40 kV with a 0.5 mm aluminum filter. For the different scans, the relative doses, tube currents, and exposure times were:</p> <ul> <li>100 % relative dose: tube current 1 mA, exposure time 2000 ms,</li> <li>50 % relative dose: tube current 1 mA, exposure time 1000 ms,</li> <li>25 % relative dose: tube current 0.5 mA, exposure time 1000 ms,</li> <li>10 % relative dose: tube current 0.2 mA, exposure time 1000 ms.</li> </ul> <p><em>Data Post-Processing</em></p> <p>Before the scans, two correction images were acquired for each scan setting. A dark current image was created by averaging 255 images taken with the X-ray source off. A flat-field image was created by averaging 255 images taken with the X-ray source switched on with no sample placed in the scanner. After the scan, dark current and flat-field corrections were applied to each projection image using the Hamamatsu HiPic imaging software version 9.3.</p> <p><em>Data Format</em></p> <p>The X-ray projections are stored in .tif format. The metadata are contained in .txt files with formatting that is both human-readable and machine-readable.</p> <p><em>Notes</em></p> <p>Due to a slightly misaligned center of rotation in the scanner, the CT reconstructions can appear blurry. It was empirically observed that this problem can be compensated for quite well by shifting each projection left by 4 pixels, using circular boundary conditions, before performing any other operations on the projections. It was also observed that the scans are not entirely aligned, with a small angular discrepancy between each reconstruction.</p> <p> </p> <p><strong>Research Group</strong></p> <p>This dataset was produced by the Inverse Problems research group at the Department of Mathematics and Statistics at the University of Helsinki, Finland: <a href="https://www.helsinki.fi/en/researchgroups/inverse-problems">https://www.helsinki.fi/en/researchgroups/inverse-problems</a>.</p> <p> </p> <p><strong>Additional Links</strong></p> <p>To get started with the data, we recommend looking at the HelTomo toolbox, specifically created for working with CBCT data collected in the Industrial Mathematics Computed Tomography Laboratory, and available at <a href="https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox">https://se.mathworks.com/matlabcentral/fileexchange/74417-heltomo-helsinki-tomography-toolbox</a>.</p> <p>Please note that this is a an entirely separate dataset from the Walnut datasets accessible at <a href="../record/1254206">https://zenodo.org/record/1254206</a> and <a href="https://doi.org/10.5281/zenodo.6986012">https://doi.org/10.5281/zenodo.6986012</a>, although both datasets have been created by the same research group.</p> <p> </p> <p><strong>Contact Details</strong></p> <p>For more information or guidance in using these datasets, please contact alexander.meaney [at] helsinki.fi.</p>
Tomographic X-ray data of a walnut
<p>This is an open-access dataset of tomographic X-ray data of a walnut. The dataset consists of the X-ray sinogram of a single 2D slice of the walnut with three different resolutions and the corresponding measurement matrices modeling the linear operation of the X-ray transform. Each of these sinograms was obtained from a measured 120-projection fan-beam sinogram by down-sampling and taking logarithms. The original (measured) sinogram is also provided in its original form and resolution.</p> <p>In addition, a larger set of 1200 projections of the same walnut was measured and a high-resolution filtered back-projection reconstruction was computed from this data; both the sinogram and the FBP reconstruction are included in the dataset, the latter serving as a ground truth reconstruction.</p> <p>Documentation of the dataset is available at <a href="https://arxiv.org/abs/1502.04064">arxiv.org/abs/1502.04064</a>. See also <a href="https://www.fips.fi/dataset.php">www.fips.fi/dataset.php</a>.</p>
Four rainout shelters around a tree in a Walnut-Pea agroforestry system
<p>Rain exclusion device made of 4 mobile rainout shelters placed around a walnut (<em>Juglans regia x nigra</em>), to study drought resistance of pea (<em>Pisum sativum</em>) in agroforestry vs pure crop. In plot A2 of Domaine de Restinclières (coordinates: 43.704274 , 3.860958). Picture taken on 2019-04-01.</p>
Large rainout shelter in a Walnut-Wheat agroforestry system
<p>A large rainout shelter made of foldable tarpaulins attached to cables in an agroforestry system (silvoarable) with hybrid walnut (<em>Juglans regia x nigra</em>) and durum wheat (<span><span><em>Triticum turgidum ssp. durum</em>) in plot A2 of Domaine de Restinclières (coordinates: 43.704274 , 3.860958). Picture taken on 2018-02-06</span></span></p>
Linked collectors and determiners for: Northern Arizona University - Walnut Canyon National Monument Collection.
Natural history specimen data linked to collectors and determiners held within, "Northern Arizona University - Walnut Canyon National Monument Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/274a3f69-3f40-4367-a60f-e84def2a8fa0">https://bionomia.net/dataset/274a3f69-3f40-4367-a60f-e84def2a8fa0</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/274a3f69-3f40-4367-a60f-e84def2a8fa0">https://gbif.org/dataset/274a3f69-3f40-4367-a60f-e84def2a8fa0</a>. Formatted as a Frictionless Data package.
1760 Walnut Burl Mallet
Modeled from Eric Sloane's [*Museum of Early American Tools*](https://www.amazon.com/Museum-Early-American-Tools-Americana/dp/0486425606/ref=sr_1_1?crid=1MDB8783EQVPS&dchild=1&keywords=museum+of+early+american+tools&qid=1613590281&s=books&sprefix=museum+of+early%2Cstripbooks%2C170&sr=1-1). Textured with [CC0 Textures](https://cc0textures.com) assets. Made with [Blender](https://blender.org). Source: Objaverse 1.0 / Sketchfab
Walnut dummy
<p>This is only one tif file from the series and corresponding json file with metadata. Just for testing purposes.</p>
Rainout shelter in a Walnut-Sorghum agroforestry system with the tarpaulin folded
<p>Picture of a rainout shelter with a fixed tunnel structure, a folded tarpaulin, and gutters to evacuate water, used in a 28 year old agroforestry system with walnut trees and arable crops in plot A2 of Domaine de Restinclières (coordinates: 43.704274 , 3.860958). Picture taken on 2023-06-29</p>
Influence of Altitudinal Gradient on the Voltinism and Generation Time of Cydia pomonella (Lepidoptera: Tortricidae) in walnut trees in northwestern Argentina
<p><span><span>11-<span> </span></span></span><em><span>Cydia pomonella L</span></em><span>. causes significant economic loss in the global fruit-growing industry. Its biology is influenced by environmental factors which have an impact on its voltinism in relation to its habitat.</span></p> <p><span>22- <span>The influence of the altitudinal gradient on the number and duration of <em>C. pomonella</em> populations on walnut trees grown at latitudes below 29° was determined. The relation between temperature and population curves was evaluated by an altitudinal gradient.</span></span></p> <p><span><span>33- </span></span><span><span><span> </span></span></span><span>A higher number of generations was quantitatively recorded in a shorter time on orchards located at lower altitudes. Walnut trees grown at higher altitudes, with lower temperatures, showed less pest pressure. The “Predictive Extension Timing Estimator”, used in several regions for the management of <em>C. pomonella</em>, does not accurately predict the length of the generation time in plantation crops at lower altitudes, requiring further studies in this area.</span></p> <p><span>44- </span><span>The results are relevant for designing of management strategies for walnut trees grown at latitudes below 29°, where environmental conditions differ considerably from other latitudes that were studied, impacting on the population dynamics of <em>C. pomonella</em>.</span></p> <p> </p>
A basket with walnut excavated at Sagiuchi site.
A basket with walnut excavated at Sagiuchi site in Minamisoma, Fukushima Prefecture, Japan. Jomon Period: About 3000 years ago, the basket was immersed in water in a hole drilled in a lowland. It is a 3D model created from photos taken on the public release date (December 16, 2016). Source: Objaverse 1.0 / Sketchfab
Walnut Oral Immunotherapy for Tree Nut Allergy
ClinicalTrials.gov study NCT01546753. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Postprandial Effects of Walnut Components Versus Whole Walnuts on Cardiovascular Disease (CVD) Risk Reduction
ClinicalTrials.gov study NCT00938340. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Activation of Brain Centers by Short-term Walnut Consumption in Obesity
ClinicalTrials.gov study NCT02673281. IPD Sharing: NO. Countries: 1. Publications: 2.
The Metabolic Effects of Short-term Walnut Consumption in Subjects With the Metabolic Syndrome
ClinicalTrials.gov study NCT00525629. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data for: Walnut PR10/Bet v1-like proteins interact with chitinase in response to anthracnose stress
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