Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
48
datasets available to search
ShareScore release 0.9.0
Dataset results
48 results for “application rates”
Crop-specific global fertilizer application rates from "Closing yield gaps through nutrient and water management"
<p>Crop-specific global maps of N, P2O5, and K2O fertilizer application rates circa the year 2000 from the following paper:</p> <p>Mueller, ND, JS Gerber, M Johnston, DK Ray, N Ramankutty, and JA Foley. 2012. Closing yield gaps through nutrient and water management. <em>Nature</em> <strong>490</strong>: 254–257</p> <p>Data are provided at five arc-minute resolution and are saved as netcdf files. Fertilizer application rates are estimated from reconciling various national and subnational data sources. See the Supplementary Information from the 2012 paper for a full description of data sources and methods. Data quality for each grid cell is described in a map layer. Files containing the text "totalcons" sum nutrient consumption across crops per grid cell, using crop harvested areas from Monfreda et al. 2008 Global Biogeochemical Cycles. For maize, wheat, and soybean N application rates, additional maps and csv files (containing the text "politboundaries") identify the political units around the world containing unique information. Crops and crop group categories are consistent with those utilized in Monfreda et al. 2008 Global Biogeochemical Cycles.</p>
Dataset for Numerical modeling of air-vented parallel plate ionization chambers for ultra-high dose rate applications
<p>Dataset for paper: Jose Paz-Martín et al., <a href="https://www.sciencedirect.com/journal/physica-medica">Physica Medica</a> <a href="https://www.sciencedirect.com/journal/physica-medica/vol/103/suppl/C">Volume 103</a>, November 2022, Pages 147-156</p> <p><a href="https://doi.org/10.1016/j.ejmp.2022.10.006">https://doi.org/10.1016/j.ejmp.2022.10.006</a></p>
Stable Modeling on Resource Usage Parameters of MapReduce Application-Figure 3. Estimate coefficients distribution of model on read rate as response of Terasort application
<p>Figure 3 shows estimate coefficients distribution of model on read rate as the response of Terasort application. The filled triangle point-up indicates the position of the minimum stable sampling time for the corresponding estimate coefficients as well as the number above it shows the exact position value. The dashed line represents the average estimated coefficient of the regression model.</p>
Fig. 1 in Evaluating the use of a low dose fipronil bait in reducing black-tailed prairie dog (Cynomys ludovicianus) fleas at reduced application rates
Fig. 1. Flea prevalence (0.0–1.0) during pre-treatment and post-treatment for (A) captured black-tailed prairie dogs (Cynomys ludovicianus); and (B) active burrows. Vertical bars indicate the 95% confidence intervals (95% CI).
Annual crop-specific management history of phosphorus fertilizer input (CMH-P) in the croplands of United States from 1850 to 2022: Application rate, timing, and method
<p>This dataset presents spatiotemporal dynamics of phosphorus (P) fertilizer management (application rate, timing, and method) at a 4km × 4 km resolution in agricultural land of the contiguous U.S. from 1850 to 2022. By harmonizing multiple data sources, we reconstructed the county-level crop-specific P fertilizer use history. We then spatialized and resampled P fertilizer use data to 4 km × 4 km gridded maps based on historical U.S. cropland distribution and crop type database developed by Ye et al. (2024).</p> <p>This dataset contains (1) P fertilizer total consumption and mean application rate at the national level (Tabular); (2) P fertilizer consumption of 11 crops at the state level (Tabular); (3) P fertilizer consumption of permanent pasture (Tabular); (4) P fertilizer consumption of non-farm at the state level (Tabular); (5) P fertilizer application rate of 11 crop types at the state level (Tabular); (6) P fertilizer application rate of 11 crop types at the county level (Tabular); (7) P fertilizer application timing ratio at the state level (Tabular); (8) P fertilizer application method ratio at the state level (Tabular); (9) Gridded maps of P fertilizer application rate based on state-level data; (10) and (11) Gridded maps of P fertilizer application rate based on county-level data; (12)-(20) Gridded maps of P fertilizer application rate for each crop.</p> <p>A detailed description of the data development processes, key findings, and uncertainties can be found in Cao, P., Yi, B., Bilotto, F., Gonzalez Fischer, C., Herrero, M., Lu, C.: Crop-specific Management History of Phosphorus fertilizer input (CMH-P) in the croplands of United States: Reconciliation of top-down and bottom-up data sources, is under review for the journal Earth System Science Data (ESSD). https://essd.copernicus.org/preprints/essd-2024-67/#discussion. </p> <p>This work is supported by the Iowa Nutrient Research Center, the ISU College of Liberal Arts and Sciences Dean's Faculty Fellowship, and NSF CAREER grant (1945036).</p> <p> </p>
N application rates from mineral fertiliser and manure
<p>Historical N application rates from mineral fertiliser and manure. Prepared for Gridded Global Crop Model Intercomparison (GGCMI) project phase 3. </p> <p>Gridded time series of fertiliser application rates are based on national and sub-national estimates for 141 individual crops for the year 2000 from Mueller et al. (2012) and national time series for five different crop groups from LUH2v2 (Hurtt et al., 2020). Gridded time series of manure application rates on cropland are based on total applied manure per grid cell from Zhang et al. (2017) and cropland extent from LUH2v2 (Hurtt et al., 2020).</p> <p>This update (v.1.1) corrects an error in the manure application rates, which was caused by a misalignment of manure data and cropland extent. Files for fertiser application rates are identical to the previous version.</p> <p> </p> <p><strong>Reference</strong></p> <p>Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., … Zhang, X. (2020). Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6. <em>Geoscientific Model Development</em>, <em>13</em>(11), 5425–5464. https://doi.org/10.5194/gmd-13-5425-2020</p> <p>Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., & Foley, J. a. (2012). Closing yield gaps through nutrient and water management. <em>Nature</em>, <em>490</em>(7419), 254–257. https://doi.org/10.1038/nature11420</p> <p>Zhang, B., Tian, H., Lu, C., Dangal, S. R. S., Yang, J., & Pan, S. (2017). Global manure nitrogen production and application in cropland during 1860–2014: a 5 arcmin gridded global dataset for Earth system modeling. <em>Earth System Science Data</em>, <em>9</em>(2), 667–678. https://doi.org/10.5194/essd-9-667-2017</p>
The effects of a clinically feasible application of low-level laser therapy on the rate of orthodontic tooth movement: A triple-blinded split-mouth randomized controlled clinical trial.
<p>Dataset for all study's analyses.</p>
Competition for nitrogen between plants and microorganisms in grasslands: Effect of nitrogen application rate and plant acquisition strategy
<p>Several studies have investigated how nitrogen (N) addition changes N competition between focal plant species and soil microorganisms; still, the impact on community-level plant-microbial N competition and the underlying mechanisms remain unclear. We conducted a short-term (4 h) <sup>15</sup>N labeling experiment in an alpine meadow subjected to 7 years of NH<sub>4</sub>NO<sub>3 </sub>additions (0, 5, 10, and 15 g N m<sup>−2</sup> year<sup>−1</sup>), by monitoring changes in soil properties (e.g., pH, Al<sup>3+</sup>, NH<sub>4</sub><sup>+</sup>, NO<sub>3</sub><sup>−</sup>), microbial biomass (MB), plant community composition, root traits (e.g., root length, root area, specific root length), as well as the plant (nine focal species and at the community level) and microbial N uptake. Change in the N competition between the nine focal plant species and microorganisms following N addition depended on the species. At the community level, the N addition rate did not affect plant-microbial competition for NH<sub>4</sub> <sup>+</sup> and NO<sub>3</sub> <sup>−</sup> (<em>P </em>> 0.05). Nitrogen addition directly decreased NH<sub>4</sub><sup>+</sup>competition (β= −0.700) but indirectly increased because of improved plant uptake due to increased N availability(β=1.214). Competition for NO<sub>3</sub><sup>−</sup> was dependent on microbial uptake (β= −0.953) and was influenced by opposing effects of increased N availability (β=1.342) and reduced MB (β= −0.439). Thus, the effects of increased soil N availability and suppressed MB on plant and microbial N competition offset each other, while the plant community had a negligible impact. Such responses should be taken into account for better predictions of the effect of N addition on net primary productivity and ecosystem stability.</p>
A Novel Hybrid Finite Element-Spectral Boundary Integral Scheme for Modeling Earthquake Cycles: Application to Rate and State Faults with Low-Velocity Zones
<p>We present a novel hybrid finite element (FE) - spectral boundary integral (SBI) scheme that enables efficient simulation of earthquake cycles. This combined FE-SBI approach captures the benefits of finite elements in modelling problems with nonlinearities, as well as the computational superiority of SBI. The domain truncation enabled by this scheme allows us to utilize high-resolution finite elements discretization to capture inhomogeneities or complexities that may exist in a narrow region surrounding the fault. Combined with an adaptive time stepping algorithm, this framework opens new opportunities for modeling earthquake cycles with high-resolution fault zone physics. In this initial study, we consider a two dimensional (2-D) anti-plane model with a vertical strike-slip fault governed by rate and state friction in the quasi-dynamic limit under the radiation damping approximation. The proposed approach is first verified using the benchmark problem BP-1 from the Southern California Earthquake Center (SCEC) sequence of earthquake and aseismic slip (SEAS) community verification effort. The computational framework is then utilized to model the earthquake sequence and aseismic slip of a fault embedded within a low-velocity fault zone (LVFZ) with different widths and compliance levels. Our results indicate that sufficiently compliant LVFZs contribute to the emergence of sub-surface events that fail to penetrate to the free surface and may experience earthquake clusters with nonuniform inter-seismic time. Furthermore, the LVFZ leads to slip rate amplification relative to the homogeneous elastic case. We discuss the implications of our results for understanding earthquake complexity as an interplay of fault friction and bulk heterogeneities. The complete work consists of all files listed below. </p>
Impact of a Smartphone Application on Postpartum Weight Loss and Breastfeeding Rates Among Low-income, Urban Women
ClinicalTrials.gov study NCT03167073. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Competition for nitrogen between plants and microorganisms in grasslands: Effect of nitrogen application rate and plant acquisition strategy
Open the record for dataset details and reuse information.
Application of an ensemble earthquake rate model in Italy, considering seismic catalogs and fault moment release - Models and Catalogs
<p>Models and Catalogs for "Application of an ensemble earthquake rate model in Italy, considering seismic catalogs and fault moment release" , Murru et al. 2020</p>
Factors used to Influence Mobile Health Application Rating
<p>Over the last five years, mobile health applications (mHealthapp) have evolved exponentially to assess and support our health and well-being. This paper presents an Artificial Intelligence (AI)-enabledmHealth app rating tool which takes multidimensional measures such as starrating, user's review and features declared by the developer to generate apprating. However, currently, there is very little conceptual understanding onhow users' reviews affect app rating from a multi-dimensional perspective. This study applies artificial intelligence (AI)-based text mining technique to develop more comprehensive understanding of users' feedback based on an array of factors, determining the mHealth app ratings. Based on the literature, six variables were identified that influence the mHealth app rating scale. These factors are user's star rating, user's text review, user interface (UI) design, functionality, security and privacy, and clinical approval. Natural Language Toolkit package is used for interpreting text and to identify the App users' sentiment. Additional considerations were accessibility, protection and privacy, UI design for people living with physical disability. Moreover, the details of clinical approval, if exists, were taken from the developer's statement. Finally, we fused all the inputs using fuzzy logic to calculate the new app rating score. Our proposed model concentrates on heart related apps found in the play store and app gallery. The findings indicate the efficacy of the model as opposed to the current device scale. This study has implications for both app developers and consumers who are using mHealth apps to monitor and track their health. The performance evaluation shows that the proposed mHealth scale has shown excellent reliability as well as internal consistency of the scale, and high inter-rater reliability index. It has been also found that the fuzzy based rating has a high variance compared to the conventional app rating whereas the fuzzy based rating shows high relationship in contrast to scoring based on expert opinion.</p>
Supplementary Material for: 'An impedance pneumography signal quality index: design, assessment and application to respiratory rate monitoring'
<p>This supplementary material accompanies:</p> <p>Charlton P.H. <em>et al.</em>, "<a href="https://doi.org/10.1016/j.bspc.2020.102339">An impedance pneumography signal quality index for respiratory rate monitoring: design, assessment and application</a>", <em>Biomedical Signal Processing and Control</em>, 65, 102339, 2021.</p> <p>The Impedance Pneumography Signal Quality Index (SQI) dataset and accompanying scripts (in Matlab format) are provided to facilitate reproduction of the analyses using data from the MIMIC III dataset in this publication.</p> <p><strong>Summary of Publication</strong></p> <p>In this article we developed and assessed the performance of a signal quality index (SQI) for the impedance pneumography signal.<br> The SQI was developed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a>, and assessed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a> and MIMIC III datasets.<br> The SQI was found to accurately classify segments of impedance pneumography signal as either high or low quality. Furthermore, when it was coupled with a high performance RR algorithm, highly accurate and precise RRs were estimated from those segments deemed to be high quality. In this study performance was assessed in the critical care environment - further work is required to deteremine whether the SQI is suitable for use with wearable sensors. Both the dataset and code used to perform this study are publicly available.</p> <p><strong>Reproducing this Publication</strong></p> <p>The work relating to the MIMIC dataset in this publication can be reproduced as follows:</p> <p><strong> - Reproducing the analysis</strong><br> These steps can be used to quickly reproduce the analysis using the curated and annotated dataset.</p> <p>* Download the curated and annotated dataset from <a href="https://doi.org/10.5281/zenodo.3973770">Zenodo</a> using this <a href="https://zenodo.org/record/3973771/files/mimic_imp_sqi_data.mat?download=1">direct download link</a>.<br> * Run the analysis using the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.</p> <p><strong> - Full reproduction</strong><br> These steps include downloading the raw data files, extracting data from these files, collating the dataset, manually annotating the data, and performing the analysis.</p> <p>* Use the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script to download raw MIMIC data files from PhysioNet, and collate them into a single Matlab file.<br> * Prepare the dataset for manual annotation by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.<br> * Manually annotate the signals by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_mimic_imp_annotation.m</em></a> script - the annotations are stored in separate files (the original annotation files are available <a href="https://zenodo.org/record/3974113/files/2019_annotations.zip?download=1">here</a>).<br> * Import the manual annotations into the collated data file by re-running the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script.<br> * Run <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> to perform the analysis described in the publication.</p> <p><strong> - Submitted manuscript</strong></p> <p>The submitted manuscript is available <a href="https://zenodo.org/record/5211463/files/Impedance%20SQI%20manuscript%20-%20Oct%202020%20revision.docx?download=1">here</a>.</p> <p>The scripts are also stored (alongside details of how to use them) are available in the <a href="http://peterhcharlton.github.io/RRest/">RRest GitHub repository</a> at: <a href="https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI">https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI</a></p> <p>License: The dataset (<a href="https://zenodo.org/record/3974113/files/mimic_imp_sqi_data.mat?download=1"><em>mimic_imp_sqi_data.mat</em></a>) is distributed under the terms specified in the accompanying LICENSE file. The scripts are distributed under the GNU General Public Licence (as specified towards the start of each file).</p> <p>Version 1.0: This version includes the submitted manuscript.</p> <p> </p>
A framework for 210Pb model selection and its application to 37 cores from Eastern Canada to identify the dynamics and drivers of lake sedimentation rates
<ul> <li>Radioisotopic and ancillary data (i.e., estimated temperature, precipitation and population in lake watersheds)</li> <li>R-code script used in the establishment of 210Pb framework along with example spreadsheet</li> </ul> <p>Original publication: Baud, A., Aulard, C., Ghanbari, H., Fradette, M., Antoniades, D., Del Giorgio, P., Huot, Y., Francus, P., Smol, J. & Gregory‐Eaves, I. (2022). A framework for 210Pb model selection and its application to 37 cores from Eastern Canada to identify the dynamics and drivers of lake sedimentation rates. Earth Surface Processes and Landforms. https:</p>
Clinical Observation of V-P Shunt and Application of "Three-step Disinfection" to Reduce Post-operative Infection Rate
ClinicalTrials.gov study NCT04785248. IPD Sharing: NO. Countries: 1. Publications: 7.
Heart Rate Assessment at Birth Comparing Stethoscope Versus Tap-based Application
ClinicalTrials.gov study NCT03913533. IPD Sharing: YES. Countries: 1. Publications: 11.
The Role of the Rate of Force Application in Responses to Spinal Manipulation Therapy
ClinicalTrials.gov study NCT02550132. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Local Gentamicin Application to Reduce Postoperative Infection Rate
ClinicalTrials.gov study NCT01287780. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Success Rate of Cryotherapy Application in Primary Molars With Signs of Irreversible Pulpitis
ClinicalTrials.gov study NCT05267847. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.