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608 results for “irrigation”

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zenodo32/100

Ultrasound-Guided Percutaneous Irrigation of Rotator Cuff Calcific Tendinopathy (US-PICT): Patient Experience

<p><strong>Purpose:&nbsp;</strong>To assess patients&#39; experience of ultrasound-guided percutaneous irrigation of rotator cuff calcific tendinopathy (US-PICT).</p> <p><strong>Methods:&nbsp;</strong>Ninety-one patients (58 females; mean age: 50.5 &plusmn; 8.3 years) treated by US-PICT (local anesthesia, single-needle lavage, and intrabursal steroid injection) answered to a list of questions regarding their experience of the procedure before treatment, immediately after treatment, and three months later. The Borg CR10 scale was used to evaluate perceived pain, discomfort during anesthetic injection, and anxiety. The Wilcoxon, Spearman&#39;s rho, linear regression, and chi-square statistics were used.</p> <p><strong>Results:&nbsp;</strong>81/91 patients complained mild discomfort during the injection of anesthetics (2, 1-2). Pain scores during US-PICT were very low (0, 0-1), with 70% patients having not experienced pain. After treatment, we found a significant reduction of pain (before: 8, 7-8; 3-month: 3, 1-6;&nbsp;<em>p</em>&nbsp;&lt; .001) and anxiety (before: 5, 2-7; during treatment: 2, 1-7;&nbsp;<em>p</em>&nbsp;= 0.010), with high overall satisfaction (immediately after: 10, 9-10; 3-month: 9, 7-10) and confidence in the possibility of recovery (immediately after: 9, 8-10; 3-month: 10, 8-10), respectively. Treatments performed before US-PICT were not statistically associated with pain relief (<em>p</em>&nbsp;= 0.389) and clinical improvement (<em>p</em>&nbsp;= 0.937). We found a correlation between satisfaction immediately postprocedure and confidence in the possibility of recovery (<em>p</em>&nbsp;= 0.002) and between satisfaction three months after treatment and clinical improvement (<em>p</em>&nbsp;&lt; 0.001) and patients&#39; reminds about the description of the procedure (<em>p</em>&nbsp;= 0.005) and of the potential complications (<em>p</em>&nbsp;= 0.035).</p> <p><strong>Conclusions:&nbsp;</strong>US-PICT is a mildly painful, comfortable, and well-tolerated procedure, regardless of any previous treatments. Patients&#39; satisfaction is correlated with clinical benefit and full explanation of the procedure and its complications.</p>

opencc-by-4.0Nov 2020View details →
dryad32/100

Irrigation well water in Nebraska: essential nutrient contents and other properties

<p>Water nutrient concentrations and other properties were surveyed by sampling water from 642 irrigation wells in Nebraska. The amount of Ca, Mg, S, Cl, and B applied in irrigation exceeds removal in 15 Mg ha<sup>-1</sup> of corn (<i>Zea mays</i> L.) grain harvest for most wells. Irrigation supply exceeded corn grain harvest removal of K, Mn and Mo for &gt;20% of the wells. The supply of P, Zn, Cu, Fe, and Mo was generally very low but sufficient with some wells to be considered in nutrient management plans. The median level of nitrate N was 4.4 ppm with 25% of the wells having &gt;10 ppm NO<sub>3</sub>-N which is above the suitability limit for human consumption. The agricultural lime equivalent applied with one or two ML of irrigation was enough to neutralize the acidifying effect of 200 kg ha<sup>-1</sup> of fertilizer-N for 70% or 89% of the wells. Nutrient and lime supply was relatively low for Sandhills wells and relatively high for wells in river valleys of &lt;100 ft depth. No wells had excessive Na levels but 0.3% of the wells had salinity levels of concern. A grouping of wells into 11 aquifer, geological formation and well-depth combinations accounted for &gt;20% of the variation for most water properties but much variation occurred within groups. Sampling of the well water is needed for full optimization of nutrient and soil management. Information on nutrients supplied through irrigation should be complemented by regular soil testing and the use of recommended nutrient management guidelines.</p>

opencc-zeroDec 2020View details →
zenodo32/100

A Dynamic Socio-hydrological Model of The Irrigation Efficiency Paradox

<p>The dataset for the journal&nbsp;article entitled:&nbsp;A Dynamic Socio-hydrological Model of The Irrigation Efficiency Paradox</p>

opencc-by-4.0Jun 2021View details →
zenodo32/100

Supporting Dataset for the study "A simple Approach to Represent Irrigation Water Withdrawals in Earth System Models"

<p><span><span>This archive contains the following information (8 directories):</span></span></p> <ol> <li> <p><span><span>surfex_v8.0climat : ISBA-CTRIP source code from CNRM-ESM-2 used in the study</span></span></p> </li> <li> <p><span><span>model_data : parameters used by the model and to plot the figures</span></span></p> </li> <li> <p><span><span>fig : ncl scripts to plot the figures &amp; figures in eps</span></span></p> </li> <li> <p><span><span>discharges : simulated and observed river discharges data</span></span></p> </li> <li> <p><span><span>fluxes : simulated water fluxes plotted on the figures</span></span></p> </li> <li> <p><span><span>tws : estimated and simulated terrestrial water storage data</span></span></p> </li> <li> <p><span><span>withdrawals : imposed (impirrig) and simulated (irrig) irrigation water withdrawals</span></span></p> </li> <li> <p><span><span>wtd : simulated and estimated groundwater levels and trends</span></span></p> </li> </ol>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Combined Effects of Future Urban Growth and Climate Change on Irrigation Water Demand in Central Arizona

<p>This dataset contains the simulation results of the combined effects of future urban growth and climate change on irrigation water use in the Phoenix Metropolitan Area, central Arizona. The simulation is conducted with the Variable Infiltration Capacity (VIC) model at 1-km, hourly resolution from 1981-2100 and aggregated to 30-yr average in this dataset.&nbsp;</p> <p>The 30-yr average results are compressed and organized into three files: <strong>Baseline</strong>, <strong>ICLUS2050</strong>, and <strong>ICLUS2100</strong>. The Baseline file contains results using the historical land cover map (year 2010). The <strong>ICLUS2050</strong> and <strong>ICLUS2100</strong> contain results using future land cover maps. The filename of modeling results contains&nbsp;the associated land cover and climate change scenario as follows: &quot;fluxes.irri.ICLUS_<em>$YEAR</em>_<em>$LCSCE</em>.<em>$CLSCE.$GCM</em>.nc&quot;, where <em>$YEAR</em> is the year of land cover change projection (2050 or 2100), <em>$LCSCE</em> is the land cover change scenario (SSP2 or SSP5), <em>$CLSCE</em> is the climate change scenario (RCP45 or RCP85), and <em>$GCM</em> is the GCM used (eight in total)&nbsp;</p> <p>More details can be found on the associated paper&nbsp;(this record will be updated when the paper is published):</p> <p>Wang, Z., and Vivoni, E.R. 2021. Combined Effects of Future Urban Growth and Climate Change on Irrigation Water Demand in Central Arizona.&nbsp;<em>Journal of the American Water Resources Association (in revision)</em>.</p>

opencc-by-4.0Jan 2022View details →
dryad32/100

Sustainable use of groundwater may dramatically reduce irrigated production of maize, soybean, and wheat

<p class="Abstract"><span><span><span><span><span><span><span><span><span><span><span>Groundwater extraction in the United States (US) is unsustainable, making it essential to understand the impacts of limited water use on irrigated agriculture. Here, we integrate a gridded crop model with satellite observations, recharge estimates, and water survey data to assess the effects of sustainable groundwater withdrawals on US irrigated agricultural production.  Our model agrees with satellite-based estimates of evapotranspiration (R<sup>2</sup> = 0.68<b>)</b>, as well as survey production estimates from the United States Department of Agriculture (R<sup>2</sup> = 0.82 – 0.94 for county-level production and 0.37 – 0.54 for county-level yield). Using the optimistic assumption that groundwater extraction equals estimated effective aquifer recharge rate, we find that sustainable groundwater use decreases US irrigated production of maize, soybean, and winter wheat by 20%, 6%, and 25%, respectively. Using a more conservative assumption of groundwater availability, US irrigated production of maize, soybean, and winter wheat decreases by 45%, 37%, and 36%, respectively. The wide range of simulated losses is driven by considerable uncertainty in surface water and groundwater interactions, as well as accounting for adaptation and the many aspects of sustainability, including environmental flows. These results demonstrate the vulnerability of US irrigated agriculture to unsustainable groundwater pumping, highlighting the difficulty of expanding or even maintaining irrigated food production in the face of climate change, population growth, and shifting dietary demands. Our findings are based on reducing pumping by fallowing irrigated farmland, so alternate pumping reduction strategies or technological advances in crop genetics and irrigation technologies could produce different results.</span></span></span></span></span></span></span></span></span></span></span></p>

opencc-zeroDec 2021View details →
dryad32/100

Cover crop and irrigation impacts on weeds and maize yield

<p>Winter cover crops (CC) may facilitate weed management by inhibiting weed seed germination and seedling emergence and suppressing weed growth within the cash crop. In southern New Mexico, with scarce winter precipitation and limited irrigation water, producing sufficient CC biomass for effective weed suppression while conserving water resources is challenging. This study assessed the water requirement to produce a CC with enough biomass for weed suppression benefits during cash crop growth at two locations in New Mexico. Three winter CC species, barley, Austrian winter pea and mustard, grown singly and in a three‐way mix, under three differential irrigation treatments (one, two or three irrigations after emergence) were evaluated for their weed‐suppressive potential. Maize was planted as a cash crop four weeks after winter CC termination. Number of irrigations had no effect on the CC and weed biomass production. All CCs had lower weed density prior to maize planting compared with fallow. Barley and the three‐way mix reduced weed density by 56–96% and 68–95%, respectively. All CC treatments had lower weed biomass at the end of critical period for weed control in maize compared with fallow. Weed biomass at maize harvest did not differ between treatments. The maize yield was consistently higher in conventionally managed, weed‐free subplots, than in unsprayed weedy subplots, suggesting that CCs did not suppress weeds throughout the maize growing season. Except for barley, CCs did not cause reductions in maize yield compared with fallow. Overall, the study suggested that with adequate winter precipitation, weed‐suppressive winter cover crop stands can be produced with just one irrigation at seeding and one supplemental irrigation, making them a viable option in water‐limited agroecosystems.</p>

opencc-zeroJan 2022View details →
zenodo32/100

Socio-demographic, institutional and governance factors influencing adaptive capacity of smallholder irrigation schemes

<p>Socio-demographic, institutional and governance factors influencing adaptive capacity of smallholder irrigation schemes</p>

opencc-by-4.0May 2022View details →
zenodo32/100

Dams for hydropower and irrigation: Trends, challenges, and alternatives

<p>Data associated with the paper "Dams for Hydropower and Irrigation: Trends, Challenges, and Alternatives" by R. J. P. Schmitt and L. Rosa (2024) in Renewable and Sustainable Energy Reviews</p> <p>Notably, global dataset of hydropower installed in major dams and reservoirs (based on Lehner B, Liermann CR, Revenga C, V&ouml;r&ouml;smarty C, Fekete B, Crouzet P, et al. High-resolution mapping of the world&rsquo;s reservoirs and dams for sustainable river-flow management. Front Ecol Environ 2011;9:494&ndash;502.)</p>

opencc-by-4.0Feb 2024View details →
zenodo32/100

Philoxenite 3D models: Irrigation chanel - area SQ4

<div> <div>The documentation has been created as part of the National Science Centre grant (UMO-2017/25/B/H3/01841).</div> </div>

opencc-by-4.0May 2024View details →
zenodo32/100

Philoxenite 3D models: Irrigation chanel - area V5

<div> <div>The documentation has been created as part of the National Science Centre grant (UMO-2017/25/B/H3/01841).</div> </div>

opencc-by-4.0May 2024View details →
zenodo32/100

Philoxenite 3D models: Irrigation chanel - area V3

<div> <div>The documentation has been created as part of the National Science Centre grant (UMO-2017/25/B/H3/01841).</div> </div>

opencc-by-4.0May 2024View details →
zenodo32/100

Development of an IoT-Based Early Warning System in Irrigation Channels to Supports Sustainable Environmental Management in Yogyakarta

<p>This material has presented on 2nd International Conference on Advanced Research in Engineering and Technology in October 25, 2023.</p>

opencc-by-4.0Jun 2024View details →
zenodo32/100

Optimizing Cucumber Growth: Integrating Smart Irrigation with various Fertilization Strategies in Greenhouse Conditions

<div> <div>Supplemental materials for:</div> <div>"Optimizing Cucumber Growth: Integrating Smart Irrigation with various Fertilization Strategies in Greenhouse Conditions", under submission.</div> <br> <div>The 'datas.xlsx' file contains tables of raw data collected from the experiment site.</div> <div>&nbsp;</div> <div>Features:</div> <div> <ul> <li>Leaf Area</li> <li>Iwp</li> <li>Photosynthesis</li> <li>Yield</li> <li>Fruit Quality</li> <li>Summary</li> </ul> </div> </div>

opencc-by-4.0Jul 2024View details →
zenodo32/100

MADFORWATER: WP3: Adaptation of technologies for efficient water management and treated wastewater reuse in agriculture: Task3.1: Reduction of crop water requirement and tools for irrigation management with treated WW: Subtask 3.1.1: Plant Growth Promotion (PGP) bacteria to enhance crop resistance to water stress and salinity

<p>This dataset contains the data underlying the following publication: Hassen W, Neifar M, Cherif H, Najjari A, Chouchane H, Driouich RC, Salah A, Naili F, Mosbah A, Souissi Y, Raddadi N, Ouzari HI, Fava F and Cherif A (2018) Pseudomonas rhizophila S211, a New Plant Growth-Promoting Rhizobacterium with Potential in Pesticide-Bioremediation. Front. Microbiol. 9:34. doi: 10.3389/fmicb.2018.00034</p>

opencc-by-4.0May 2018View details →
zenodo32/100

Irrigation water salinity impacts Date palm leaf fungi

Open the record for dataset details and reuse information.

opencc-by-4.0Sep 2024View details →
zenodo32/100

A Spatiotemporal Dataset of Irrigated Agricultural Areas Across the Coastal Plain Region of South Carolina; USA

<p>A Spatiotemporal Dataset of Irrigated Agricultural Areas Across the Coastal Plain Region of South Carolina; USA</p>

opencc-by-4.0Oct 2021View details →
zenodo32/100

Players' decisions data for exit-voice irrigation experiment

<p>This data contains the decisions data of human-subject players who participated in the irrigation exit-voice experiment.&nbsp;</p>

opencc-by-4.0Nov 2022View details →
zenodo32/100

Crop diversification and digestate application effect on the productivity and efficiency of irrigated winter crop systems

<p>This dataset was done gathering and calculating data from an experiment integrated in the Circular Agronomics project. In October 2019 an experiment was setup in a randomized block design where 5 different irrigated winter crops were grown in 2 3-year rotations by 3 seasons. Several crop and and soil variables were measured to test for responses under different fertiliser treatments, including untreated and dried acidified digestates. There were also different crop precedents especifically for wheat, since this was the common crop between both rotations (cereal and diverse). With the gathered data we were able to calculate and test for differences in grain yield and N concentration, N uptake efficiency and water use efficiency of the different crops under different fertilisation and rotation (wheat) treatments. Also the soil was tested for differences in soil nitrates at 3 time points during the 3 seasons and soil total nitrogen at the end of the experiment. (Start: 2019-09-20 ; End: 2022-08-30)</p>

opencc-by-4.0Dec 2022View details →
zenodo32/100

Validation of a new global irrigation scheme in the ORCHIDEE land surface model - Dataset

<p>Datasets used in the paper &#39;Validation of a new global irrigation scheme in the ORCHIDEE land surface model&#39;, submitted to GMD</p>

opencc-by-4.0Jun 2023View details →

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dandi-nwb
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Last verified 2026-04-30Open record

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.

ibl
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Last verified 2026-04-29Open record

OpenNeuro

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openneuro
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Last verified 2026-04-29Open record