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852 results for “grain”
Figure 4 in Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan
Figure 4. Scree plot of principal components against eigenvalues.
Figure 2 in Statistical modeling for analyzing grain yield of durum wheat under rainfed conditions in Azad Jammu Kashmir, Pakistan
Figure 2. The plot of residuals versus fitted values.
Dumps and Data for 'Compaction during fragmentation and bouncing produces realistic dust grain porosities in protoplanetary discs'
<div>This dataset contains the files required to recreate the Phantom simulations run in the publication Michoulier et al. 2024, A&A 688, A31.</div> <div>We have also included the dumps required to re-create Figures 10, 11, 14, 15, 16, D.1 and E.1.</div>
A direct comparison of single grain and multi-grain aliquot measurements of feldspars from colluvial deposits in KwaZulu-Natal, South Africa
<p>This dataset accompanies a manuscript intended for submission to the journal Geochronology. The dataset includes the raw luminescence data (.binx format) generated during equivalent dose measurements of all samples, for single grain and multi-grain aliquot measurements. It also includes the .RDS files, which are the output of bayesian modelling using BayLum. Furthermore, the dataset includes the Rcodes used for bayesian modelling, as well as to generate the standardised growth curves and the application of the LnTn method. The dataset is accompanied by a .txt file, which contains information on file labelling, measurement conditions, and the R codes developed/used as part of the study.</p>
Data for: Coarse-Grained Simulations of Columnar Ionic Liquid Crystals: Comparison with Experiments
<p>This repository contains the python scripts required for running coarse-grained simulations of columnar ionic liquid crystals, as detailed in the corresponding manuscript. The scripts have been tested with HOOMD-blue v.2.9.7 and python v.3.9.</p> <ul> <li>The script "equilibration_run_npt.py" performs the initial equilibration in the NPT ensemble using an isotropic barostat at atmospheric pressure.</li> <li>The script "production_run_nvt.py" performs the production run in the NVT ensemble.</li> </ul> <p>Both scripts take two input parameters from the command line, that is the name of the start configuration and the temperature T. For example, use the command "python3 production_run_nvt.py ILC8_303.0K_end_production.gsd 303" to load the file "ILC8_303.0K_end_production.gsd" and perform a production run at T=303K.</p> <p>In addition, we have included the final snapshots of our simulations in the .gsd format (https://gsd.readthedocs.io/). The file name indicates the specific ILC molecule and temperature, at which it was simulated. For example, the file "ILC8_303.0K_end_production.gsd" contains the final frame of the NVT simulations of the molecule ILC-8 at temperature T=303K.</p>
Plant Growth Regulators in Barley in Northern Grains Region Australia
<p><strong>Project title: </strong>NGN Validating the use of plant growth regulators to manage excessive growth in barley in Northern Region warm growing environments (2022-24, AMP2205-004RTX). </p> <p><strong>Methodology: </strong>Seven barley PGR trials were run in 2022-23 at a range of locations in northern NSW. In 2022, three trials assessed PGRs Moddus Evo<sup>®</sup> (250 g/L Trinexapac-Ethyl) and ethephon (Promote<sup>®</sup> Plus 900, 900 g/L Ethephon) and a range of use patterns across 4 barley varieties. Following high levels of lodging in 2022, four trials in 2023 quantifed the impact of PGR treatments on different varieties, times of sowing and nitrogen levels. </p> <p>Four varieties – Leabrook, Laperouse, Planet, Maximus CL – were selected to represent the range of lodging susceptibilities in commercial barley varieties. Moddus Evo<sup>®</sup> and ethephon use patterns were tested to allow for early and late control of barley biomass production as well as bounce back, where compensatory growth occurs under favourable conditions following a PGR application (Table 1).</p> <p><a name="_Ref165987766"></a>Table 1. PGR use patterns tested on dryland barley in 2022 and 2023</p> <table> <tbody> <tr> <td> <p><strong> </strong></p> </td> <td> <p><strong>Application 1</strong></p> </td> <td> <p><strong>Application 2</strong></p> </td> </tr> </tbody> <tbody> <tr> <td> <p><strong>PGR Treatment Name</strong></p> </td> <td> <p><strong>PGR</strong></p> </td> <td> <p><strong>Rate (ml)</strong></p> </td> <td> <p><strong>GS</strong></p> </td> <td> <p><strong>PGR</strong></p> </td> <td> <p><strong>Rate (ml)</strong></p> </td> <td> <p><strong>GS</strong></p> </td> </tr> <tr> <td> <p>Moddus 31</p> </td> <td> <p>Moddus Evo<sup>®</sup></p> </td> <td> <p>400</p> </td> <td> <p>31</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Moddus 300 @ 31</p> </td> <td> <p>Moddus Evo<sup>®</sup></p> </td> <td> <p>300</p> </td> <td> <p>31</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Moddus 37</p> </td> <td> <p>Moddus Evo<sup>®</sup></p> </td> <td> <p>400</p> </td> <td> <p>37</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Moddus 31 + 37</p> </td> <td> <p>Moddus Evo<sup>®</sup></p> </td> <td> <p>400</p> </td> <td> <p>31</p> </td> <td> <p>Moddus Evo<sup>®</sup></p> </td> <td> <p>400</p> </td> <td> <p>37</p> </td> </tr> <tr> <td> <p>Ethephon 41</p> </td> <td> <p>Ethephon*</p> </td> <td> <p>400</p> </td> <td> <p>41</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>Ethephon 45</p> </td> <td> <p>Ethephon*</p> </td> <td> <p>400</p> </td> <td> <p>45</p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p> </p> </td> </tr> </tbody> </table> <p>GS=Growth Stage; 900 g/L Ethephon</p> <p>In 2022, the impact of PGR treatments (n=6) on four barley varieties were tested at three locations in northern NSW (Table 2 and Table 3).</p> <p>1. At Boomi and Gurley a variety (n=4) by PGR strategy (n=5) full factorial plot trial was established. Due to high rainfall and subsequent waterlogging the trial planted at Boomi failed to establish.</p> <p>2. At Tulloona a trial was established to replace the failed Boomi trial. PGR treatments (n=5) were applied over a commercial crop of Planet barley in a randomised complete block design.</p> <p>3. At Spring Ridge, a partial factorial experiment assessing varieties (n=4) was established with 6 PGR treatments.</p> <p>In 2023 trial sites were established at Boomi, Gurley, Pallamallawa and Breeza.</p> <p><span><span>4. </span></span>At Boomi full replicated randomised incomplete block design trials assessed the impact of time of sowing (n=2, early and mid time of sowing) and PGRs (n=6) for four barley cultivars. For the first time of sowing, PGRs (n=6) were applied to four varieties; Leabrook, Laperouse, Planet and Maximus CL, at the second time of sowing PGRs were only applied to lodging susceptible variety Leabrook.</p> <p>5. At Gurley, the same trial was repeated as describe above for Boom</p> <p>6. At Breeza, the four barley cultivars were tested with six PGR treatments with one time of sowing only.</p> <p>7. At Pallamallawa, Leabrook was planted with four nitrogen rates (0, 75, 150 and 250 kg N/ha) applied as urea-N and six PGR treatments were applied. This trial failed due to residual herbicide damage and thus the results from this trial are not presented in this report. Consequently, yield responses to PGR treatment under a range of nitrogen levels was unable to be captured in this project.</p> <p>Seasonal conditions in 2022 and 2023 differed markedly for both in-crop temperatures and rainfall. In 2022, cooler than average spring maximum temperatures were experienced at Tulloona and Gurley while at Spring Ridge maximum spring temperatures were warmer than average. In contrast, in 2023 maximum winter and spring temperatures were 1.5<span>⁰</span>C higher than monthly averages between June and October (Appendix A).</p> <p>There were large differences in annual and growing season rainfall (May-October, GSR) between 2022 and 2023 (Table <span>4</span><span></span>). In 2022, annual rainfall was 62-241mm above the long term average while in 2023 annual rainfall was 163-195mm below the long-term average. More importantly, were the differences in growing season rainfall. In 2022 growing season rainfall was 202-242mm above average (Decile 10) while in 2023 it was 136-175mm below average (Decile 1). However, high levels of soil water in 2023 compensated for the lack of in-crop rain.</p> <p><a name="_Ref167779013"></a>Table <span><span>4</span></span>. Plant available water and rainfall data for barley PGR trials in 2022 and 2023</p> <table> <tbody><tr> <td> <p><strong><span>Site</span></strong></p> </td> <td> <p><strong><span>Trial</span></strong></p> </td> <td> <p><strong><span>Planting PAW (mm)</span></strong></p> </td> <td> <p><strong><span>Annual rainfall (mm) </span></strong></p> </td> <td> <p><strong><span>Annual rainfall (mm)</span></strong></p> </td> <td> <p><strong><span>Growing season rainfall (mm)*</span></strong></p> </td> <td> <p><strong><span>Growing season rainfall (mm)*</span></strong></p> </td> </tr> </tbody><tbody> <tr> <td> <p><strong><span> </span></strong></p> </td> <td> <p><strong><span> </span></strong></p> </td> <td> <p><strong><span> </span></strong></p> </td> <td> <p><strong><span>Year of trial</span></strong></p> </td> <td> <p><strong><span>Long Term Average</span></strong></p> </td> <td> <p><strong><span>Year of trial</span></strong></p> </td> <td> <p><strong><span>Long Term Average</span></strong></p> </td> </tr> <tr> <td> <p><span>Tulloona</span></p> </td> <td> <p><span>PGR over </span><span>commercial crop</span></p> </td> <td> <p><span>165</span></p> </td> <td> <p><span>754</span></p> </td> <td> <p><span>548</span></p> </td> <td> <p><span>456</span></p> </td> <td> <p><span>214</span></p> </td> </tr> <tr> <td> <p><span>Gurley</span></p> </td> <td> <p><span>PGR x Variety</span></p> </td> <td> <p><span>165</span></p> </td> <td> <p><span>622</span></p> </td> <td> <p><span>560</span></p> </td> <td> <p><span>406</span></p> </td> <td> <p><span>204</span></p> </td> </tr> <tr> <td> <p><span>Spring Ridge</span></p> </td> <td> <p><span>PGR x Variety</span></p> </td> <td> <p><span>202</span></p> </td> <td> <p><span>870</span></p> </td> <td> <p><span>629</span></p> </td> <td> <p><span>465</span></p> </td> <td> <p><span>254</span></p> </td> </tr> <tr> <td> <p><span>Boomi</span></p> </td> <td> <p><span>PGR x Variety </span><span>x 2 Times of Sowing</span></p> </td> <td> <p><span>201</span></p> </td> <td> <p><span>367</span></p> </td> <td> <p><span>543</span></p> </td> <td> <p><span>50</span></p> </td> <td> <p><span>201</span></p> </td> </tr> <tr> <td> <p><span>Gurley</span></p> </td> <td> <p><span>PGR x Variety </span><span>x 2 Times of Sowing</span></p> </td> <td> <p><span>198</span></p> </td> <td> <p><span>365</span></p> </td> <td> <p><span>560</span></p> </td> <td> <p><span>68</span></p> </td> <td> <p><span>204</span></p> </td> </tr> <tr> <td> <p><span>Breeza</span></p> </td> <td> <p><span>PGR x Variety</span></p> </td> <td> <p><span>253</span></p> </td> <td> <p><span>484</span></p> </td> <td> <p><span>647</span></p> </td> <td> <p><span>122</span></p> </td> <td> <p><span>265</span></p> </td> </tr> <tr> <td> <p><span>Pallamallawa#</span></p> </td> <td> <p><span>PGR x Nitrogen</span></p> </td> <td> <p><span>171</span></p> </td> <td> <p><span>459</span></p> </td> <td> <p><span>641</span></p> </td> <td> <p><span>58</span></p> </td> <td> <p><span>233</span></p> </td> </tr> </tbody> </table> <p><span>*Measured as rainfall from May to October, #Trial failed due to residual herbicide damage </span></p> <p>Plant height was measured during early grain fill in each replicate from ground level to the top of the spike excluding awns of the main tiller. Lodging was scored visually with a 0 for no lodging and 10 for 100% of the crop completely lodged and flat against the ground. In 2023 no lodging was evident at Boomi, Gurley or Pallamallawa thus scores were not recorded. Biomass cuts were taken at GS 30, GS 55 and GS 99 at 30mm above ground level with 1 x 0.5m quadrat. <span> </span></p>
Crater diameter of granular polystyrene layer with various diameter of grains and Weber number of water droplet
<p>Datas about experiments of impacts made in 2021-2023. A water droplet impacting a polystyrene granular layer of 4 differents grains diameters. These datas give the crater diameter obtain in function of the Weber number of the droplet. A file from tomography of the granular layer before impact is added.</p>
Solar wind access to grains in the upper layer of regolith
<p>The directory contains the scripts and output files from running COUPI DEM for determining the distribution of protons in upper layer of regolith. This is the model data for the paper "Solar wind access to grains in the upper layer of regolith" accepted to JGR Planets.</p> <p>Each case represents different packing density. The cases are described by Paul Duvoy in file Cases_paul_duvoy.xlsx.</p> <p>Most scripts to extract and process modeled data are located in utils and<br> gnuplot directory.</p> <p> </p>
Steel, fcc precipitates in a bcc grain, EBSD
<p>The EBSD map is taken from a steel sample, from a region within a single bcc grain containing fcc precipitates after heat treatment. The sample is provided from Wiesław Świątnicki (Warsaw University of Technology). </p> <p> </p>
The Delta Maintainability Model: Measuring Maintainability of Fine-Grained Code Changes Technical Report
<p>Technical Report and dataset for "The Delta Maintainability Model: Measuring Maintainability of Fine-Grained Code Changes" submitted to the 2nd International Conference on Technical Debt (TechDebt 2019) - Montréal, Canada - May 26–27, 2019.</p>
Experimental data of an article on the impact of coarse-grain protrusion on near-bed hydrodynamics
<p>This deposit contains experimental data related to the article entitled " impact of coarse-grain protrusion on near-bed hydrodynamics" that will be publised in Journal of Geophysical Research - Earth surface. It consists in post-processed data (turbulence statistics) for flows around hemispheres protruding from a bed of fine sediments. Calculated statistics (time-averaged and double-averaged) are provided along other inferred quantities (friction velocity, etc...) and experimental parameters (protrusion level, discharge, etc..) in matlab metadata format. Matlab functions are given to plot all the figures of the article.</p>
Analytical Electron Microscopy of Grain Boundary Segregation: Application to Al-Zn-Mg-Cu (7xxx) Alloys - Supporting Data
<p>Data to reproduce the figures reported in the manuscript Analytical Electron Microscopy of Grain Boundary Segregation: Application to Al-Zn-Mg-Cu (7xxx) Alloys. Published open access in Materials Characterization <a href="https://doi.org/10.1016/j.matchar.2019.06.016">https://doi.org/10.1016/j.matchar.2019.06.016</a></p>
Drug-membrane transfer free energies for coarse-grained trimers and tetramers
<p>The databases contain drug-membrane transfer free energies for coarse-grained Martini trimers and tetramers inserted in a one-component DOPC membrane. We also provide a database of atomistic-resolution compounds mined from the GDB and that map to trimers.</p>
3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning techniques
<p>This repository contains supplementary data to the simulations in our paper</p> <p>"3D nanostructural characterisation of grain boundaries in atom probe data utilising machine learning techniques"</p> <p><strong>APTTipCarvingExecutable.tar.gz</strong><br> Contains the production state of the tip synthesis tool source code and compilation</p> <p><strong>TAPSimExecutable.tar.gz</strong><br> Contains the production state of the TAPSim simulation tool source code and compilation</p> <p><strong>scripts.zip</strong><br> Contains tiny shell scripts we used to execute the simulations</p> <p><strong>Two production simulations were performed.</strong><br> Both use the same tip bicrystal geometry but different orientations:<br> <strong>SimID.31054 is the one we discuss in the paper, it has the experimentally measured orientations</strong><br> SimID.31053 is an exemplary simulation with two different crystal orientations</p> <p><strong>For both SimID results five TAR archives exist:</strong><br> TAPSimDetectorHits* contains the main result, the simulated detector hit positionsBiCarving*<br> TAPSimTrajectories* contains all ion trajectories<br> TAPSimInput* contains supplementary results of the TAPSim field evaporation simulation<br> BiCarving* contains the settings and results of the synthesis, the XML file inside the archive details the orientations<br> Meshgen* contains the results of the meshing process prior to the TAPSim simulation</p> <p> </p>
Resolution limit of data-driven coarse-grained models spanning chemical space
<p>This repository contains all databases referenced in the supporting information of the paper titled "Resolution limit of data-driven coarse-grained models spanning chemical space" by Kiran H. Kanekal and Tristan Bereau.</p>
High-level Synthesis of Fine-grained Weakly Consistent C Concurrency
<p>This repository consists of all the experimental data of PhD thesis funded by EPSRC. </p>
X-ray computed tomography reveals that grain protrusion controls entrainment shear stress for entrainment of fluvial gravels: Dataset
<p>This is the dataset that accompanies a paper in Geology:</p> <p>Hodge RA, Voepel H, Leyland J, Sear DA, Ahmed S (2020). X-ray computed tomography reveals that grain protrusion controls entrainment shear stress for entrainment of fluvial gravels. Geology, 48(2), 149-153.</p> <p>The aim of this work was to understand how the properties of a sediment grain in a river bed affect the forces required to entrain that grain. This dataset presents the properties of 1055 sediment grains, which were meaured using CT scanning.</p>
FIGURE 9 in Angiosperm pollen grains from the Cuayuca Formation (Late Eocene to Early Oligocene), Puebla, Mexico
FIGURE 9. Index taxa recovered from the Cuayuca Formation, Puebla.
Experimental data used in the article entitled "Engineering an ultra-fine grained microstructure, twins and stacking faults in PBF-LB/M Al-Si alloy via KoBo extrusion method"
<p>Dataset include</p> <p>EBSD results: KOB;O.ang and LPBF_condition.ang</p> <p>Tensile test results:</p> <p>KOBO-processed sample: KOBO.xls</p> <p>LPBF sample: SLM.xls</p>
Experimental dataset for the publication "Characterisation of Microstructure and Special Grain Boundaries in LPBF AlSi10Mg Alloy Subjected to the KoBo Extrusion Process"
<p>Dataset includes:</p> <p>EBSD data:</p> <p>KOBO.ang - KOBO-processed sample</p> <p>LPBF_condition.ang - As-built sample</p> <p>TKD data:</p> <p>TKD_KOBO.ang - KOBO-processed sample</p> <p>HRTEM images:</p> <p>Fig. 12(b).dm3 - KOBO-processed sample</p>
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