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15 results for “grain growth”
Data from "The first ALMA survey of protoplanetary discs at 3 mm: demographics of grain growth in the Lupus region"
<p>Table 1 and Table 2 from Tazzari et al., 2021, "The first ALMA survey of protoplanetary discs at 3 mm: demographics of grain growth in the Lupus region", Monthly Notices of the Royal Astronomical Society, arXiv:2010.02248</p> <p>Both tables are available in IPAC format, which is in human- and machine-readable:</p> <pre><code class="language-python">from astropy.io import ascii tb = ascii.read('Table1.txt', format='ipac')</code></pre> <p>Table comments (stored at the beginning of the ASCII file as lines starting with "/") can be read as:</p> <pre><code class="language-python">tb.meta['comments'] </code></pre> <p> </p>
Data from "Multi-wavelength continuum sizes of protoplanetary discs: scaling relations and implications for grain growth and radial drift"
<p>Table 1, Table 2, and Table 3 from Tazzari et al., 2021, "Multi-wavelength continuum sizes of protoplanetary discs: scaling relations and implications for grain growth and radial drift", Monthly Notices of the Royal Astronomical Society, arXiv:2010.02249</p> <p>Both tables are available in IPAC format, which is in human- and machine-readable:</p> <pre><code class="language-python">from astropy.io import ascii tb = ascii.read('Table1.txt', format='ipac')</code></pre> <p>Table comments (stored at the beginning of the ASCII file as lines starting with "/") can be read as:</p> <pre><code class="language-python">tb.meta['comments'] </code></pre>
Data from: Promoting success in thin layer sediment placement: effects of sediment grain size and amendments on salt marsh plant growth and greenhouse gas exchange
<p>Thin layer sediment placement (TLP) is a method to mitigate factors resulting in loss of elevation and severe alteration of hydrology, such as sea level rise and anthropogenic modifications, and prolong the lifespan of drowning salt marshes. However, TLP success may vary due to plant stress associated with reductions in nutrient availability and hydrologic flushing or through the creation of acid sulfate soils. This study examined the influence of sediment grain size and soil amendments on plant growth, soil and porewater characteristics, and greenhouse gas exchange for three key US salt marsh plants: <em>Spartina alterniflora, Spartina patens, </em>and <em>Salicornia pacifica. </em>We found that bioavailable nitrogen concentrations (measured as extractable NH<sub>4</sub><sup>+</sup>-N) and porewater pH and salinity were found to have an inverse relationship with grain size, while soil redox was more reducing in finer sediments. This suggests that utilizing finer sediments in TLP projects will result in a more reduced environment with higher nutrient availability, while larger grain-sized sediments will be better flushed and oxidized. We further found that grain size had a significant effect on vegetation biomass allocation and rates of gas exchange, although these effects were species-specific. We found that soil amendments (biochar and compost) did not subsidize plant growth but were associated with increases in soil respiration and methane emissions. Biochar amendments were additionally ineffective in ameliorating acid sulfate conditions. This study uncovers complex interactions between sediment type and vegetation, emphasizing limitations of soil amendments. The findings aid restoration project managers in making informed decisions regarding sediment type, target vegetation, and soil amendments for successful TLP projects.</p>
Three-dimensional in-situ imaging of single-grain growth in polycrystalline In2O3:Zr films
<p>Original data</p> <p>Here, we image a single-grain growth during the amorphous-to-polycrystalline transition in technologically relevant transparent conductive oxide (TCO) film of In<sub>2</sub>O<sub>3</sub>:Zr with <em>in-situ</em> Bragg coherent X-ray diffraction imaging.</p> <p>Data was obtained at 34ID-C end-station at Advanced Photon Source, Argonne National Laboratory (USA).</p> <p>Repository contains all raw datasets of the BCDI measurements, .spec files with corresponding meta-data, and .xlsx table with information on scan numbers related to annealing steps of the sample.</p>
Capillary-driven anisotropic abnormal sub-grain growth (AGG2D)
<p><strong>Further details in the TopologyTracer documentation</strong><br> https://github.com/mkuehbach/TopologyTracer/tree/master/docs/build</p> <p><strong>Further details microstructure synthesis in the IMMMicrostructur generator documentation</strong><br> https://github.com/GraGLeS/IMM_MicrostructureGenerator/tree/master/docs/build/html</p> <p><strong>Repository content</strong></p> <p><strong>With an approximate total of 1TB the entire data set to upload is not practically feasible.<br> Instead, these data should be seriously requested from me directly.</strong></p> <p> </p> <p>0Synthesis.zip --- Microstructure synthesis<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds and MicrostructureDiagnostics.uds meta data for the grains<br> -parameters.xml parameterization of microstructure synthesis<br> -Scripts and additional input referred to by parameters.xml</p> <p>1Coarsening.zip --- Simulation<br> -Container.raw 3D implicit x,y,z right-handed coordinate system ID field describing the microstructure IDs refer to<br> -Microstructure.uds meta data for the grains<br> -VoxelizedParameters.xml parameterization of coarsening simulation<br> -NrGrains&EnergyStatistics.dat descriptive stats simulation (Time step, Real time, number of grains, ---, grid size)<br> -Network.zip implicit 3d x,y,z unsigned int ID container detailing the microstructure</p> <p>2DataAnalysis*<br> -All other archive Matlab analysis scripts and processed through TopologyTracer results.<br> Individual *.mat files to re-establish state upon Matlab exiting.</p>
Fig. 1 in Potential population growth of Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae) under six constant temperatures on grain sorghum (Sorghum bicolor L.)
Fig. 1. Age-specific survivorship (proportion of alive individuals per day) of Melanaphis sacchari under 6 constant temperatures on grain sorghum.
Fig. 2 in Potential population growth of Melanaphis sacchari (Zehntner) (Hemiptera: Aphididae) under six constant temperatures on grain sorghum (Sorghum bicolor L.)
Fig. 2. Melanaphis sacchari constant temperature dependent development rate Lactin model estimation. Solid line representing the predicted values by Logan-Lactin model and dots represent the observed values.
Data from: Promoting success in thin layer sediment placement: effects of sediment grain size and amendments on salt marsh plant growth and greenhouse gas exchange
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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>
Data from: Subgrain-controlled grain growth in laser melted 316L promoting strength at high temperatures
Stainless steel 316L prepared by laser melting consisted of hierarchical austenitic microstructure with micron sized (10-25 µm) grains containing fine 1µm subgrains with a cellular structure. At high temperature thermal treatments (≥ 1100 °C), merging and growth of the 1 µm subgrains into bigger subgrains restricted the rapid grain growth and microstructure coarsening. Partial phase transformation of austenite to ferrite at temperatures ≥ 1100 °C in combination with gradual and steady growth of subgrains inside the micron sized grains and nucleation of sigma phase have promoted the tensile strength of stainless steel 316L to 300 MPa at 1100 °C compared to conventionally made 316L counterparts with tensile strength of approximately 40 MPa. The grain growth mechanism of laser melted microstructure can change the application criteria for 316L and expand the application fields for 316L.
Data from: Subgrain-controlled grain growth in laser melted 316L promoting strength at high temperatures
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Effect of planting density on growth characteristics and grain yield increase in successive cultivations of two rice (Oryza sativa L.) cultivars
<p><span>Rice (<i>Oryza sativa</i> L.) re-cultivation plays an important role in increasing land productivity and efficiency in crop rotation. Planting density (PD) is an important agronomic factor to achieving maximum grain yield (GY). The current study aimed to determine the best PD for the first cultivation and re-cultivation of rice. The experiment was conducted as a split plot based on the randomized complete block design with three replications at Ghaemshahr University, Mazandaran (northern Iran) from 2013 to 2014. Treatments consisted of cultivar, i.e. Tarom Hashemi and Koohsar, at two levels as the main factor and PDs at the three levels of 16, 25, and 33.3 hills m<sup>-2</sup> with planting spaces of 25 × 25, 20 × 20, and 30 × 10 cm<sup>2</sup>, respectively, as the sub factor. The results of the current study showed that cultivar for the first cultivation, and year for the re-cultivation had a significant effect on GY. PD had a significant effect on GY in both first cultivation and re-cultivation. The GY of Hashemi in the first cultivation (36.1%) and re-cultivation (18.5%) was higher than that of Koohsar. GY in the first cultivation and re-cultivation had an increasing trend; PD increased up to 33.3 hills m<sup>-2</sup> as 19.9% and 21.4% in the first cultivation and re-cultivation, respectively, due to the increase in number of panicles m<sup>-2</sup> (30.1% and 30.6%, respectively). Hashemi is suitable for the first cultivation. It is noteworthy, also, that a density of 33.3 hills m<sup>-2</sup> is recommended for the first cultivation and re-cultivation.</span></p>
Figure 1 in Effect of three insect growth regulators on certain biological aspects of the lesser grain borer, Rhyzopertha dominica (Coleoptera: Bostrichidae)
Figure 1. Mean developmental period of Rhyzopertha dominica on wheat grains treated with different concentrations of insect growth regulators (IGRs).
Figure 2 in Effect of three insect growth regulators on certain biological aspects of the lesser grain borer, Rhyzopertha dominica (Coleoptera: Bostrichidae)
Figure 2. Mean percent weight loss in wheat treated with different concentrations of insect growth regulators (IGRs).
Effect of planting density on growth characteristics and grain yield increase in successive cultivations of two rice (Oryza sativa L.) cultivars
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