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Dataset results
16 results for “large-scale control”
Data from a Large-Scale Experiment to Evaluate the Effects of Trapping to Control Muskrats (Ondatra zibethicus) in The Netherlands
<p>This data set supports the publication 'A Large-Scale Experiment to Evaluate the Effects of Trapping to Control Muskrats (Ondatra zibethicus) in The Netherlands' by Daan Bos, Emiel van Loon, Erik Klop and Ron Ydenberg. (the paper was accepted for publication in Wildlife Society Bulletin in 2020)</p> <p>The Muskrat is an invasive species in Europe and in the Netherlands muskrat burrowing can compromise the integrity of dykes and hence poses a public safety threat. For that reason a control programme has been in effect since the arrival of the species in 1941. To investigate the relation between catch and effort and enhance prediction models, a large randomized controlled experiment was designed and conducted from 2013 till 2016. The publication by Bos et al. (2020) analyses the experimental results and here we present and document the experimental data. See the readme.md file for further information.</p>
Effectively controlling for sample relatedness in large-scale GWAS: application to 79 EHR-derived longitudinal traits
<p><span>Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPA<sub>GRM</sub>, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPA<sub>GRM</sub> can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid strategy incorporating saddlepoint approximation greatly increases the accuracy to analyze low-frequency and rare genetic variants, especially in unbalanced phenotypic distributions. We also introduce SPA<sub>GRM(CCT)</sub> to aggregate the results following different models via Cauchy combination test. Extensive simulations and real data analyses demonstrated that SPA<sub>GRM</sub> maintains well-controlled type I error rates and SPA<sub>GRM(CCT)</sub> can serve as a broadly effective method. Applying SPA<sub>GRM</sub> to 79 longitudinal traits extracted from</span><span> </span><span>UK Biobank primary care data, we identified 7,463 genetic loci, making a pioneering attempt to conduct GWAS for these traits as longitudinal traits.</span></p>
Data from: Environment and host as large-scale controls of ectomycorrhizal fungi
Explaining the large-scale diversity of soil organisms that drive biogeochemical processes—and their responses to environmental change—is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is—to our knowledge—unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.
Large-scale saliva pooling as a screening strategy to control transmission_raw data
<p>This dataset include the raw data of our experience after building a bespoke laboratory to control critical areas by pooling samples of saliva. From August 2020 to February 2022; 928,528 individual self-samples of saliva were processed in 52,580 pools, 4,935 of which were positive and helped us detect 5,806 nonsymptomatic individuals. </p> <p>The dataset was collected directly from the laboratory information system and was processed to delete the columns with sensitive information.</p> <p>The Dataset was charged as XLSX file and only need a compatible software.</p> <p>To facilitate the understanding of the data set, which uses the Galician language and an internal nomenclature of our laboratory, we include a sheet named "description" and a README file in which it defines the terms used and their equivalence with those used in the article.</p>
Data from: Environment and host as large-scale controls of ectomycorrhizal fungi
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Large-scale multi-trophic co-response models and environmental control of pelagic food webs in Québec lakes
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The appendix for evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach
<p><strong>Appendix I</strong>: The program of evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach</p> <p><strong>Appendix II</strong>: The sensitivity analysis of evaluating the impact of large-scale nucleic acid testing and home quarantine on COVID-19 prevention and control: a dynamic modeling approach</p>
Data from: Hierarchical power control of a large-scale wind farm by using a data-driven optimization method
<p><span>With the participation in automatic generation control (AGC), a large-scale wind farm should distribute the real-time AGC signal to numerous wind turbines (WTs). This easily leads to an expensive computation for a high-quality dispatch scheme, especially considering the wake effect among WTs. To address this problem, a hierarchical power control (HPC) is constructed based on the geographical layout and electrical connection of all the WTs. Firstly, the real-time AGC signal of the whole wind farm is distributed to multiple decoupled groups in proportion of their regulation capacities. Secondly, the AGC signal of each group is distributed to multiple WTs via the data-driven surrogate-assisted optimization, which can dramatically reduce the computation time with a small number of time-consuming objective evaluations. Besides, a high-quality dispatch scheme can be acquired by the efficient local search based on the dynamic surrogate. The effectiveness of the proposed technique is thoroughly verified with different AGC signals under different wind speeds and directions.</span></p>
Large-scale Prospective Double-blind Randomized Controlled Trial of Pecs II Block for Breast Surgery
ClinicalTrials.gov study NCT02544282. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Hierarchical power control of a large-scale wind farm by using a data-driven optimization method
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Large-scale Brain Organization During Cognitive Control in ADHD
ClinicalTrials.gov study NCT04349917. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Non-Invasive Brain Stimulation to Control Large-Scale Brain Networks
ClinicalTrials.gov study NCT04680481. IPD Sharing: YES. Countries: 1. Publications: 0.
Efficacy Comparison Between Independent Auscultation by Primary Care Physicians and AI-Assisted Auscultation in Large-scale Screening for Congenital Heart Disease: A Cluster Randomized Controlled Tria
ClinicalTrials.gov study NCT06791109. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Data from: Ecological traps for large-scale invasive species control: predicting settling rules by recolonising American mink post-culling
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A Randomized Controlled Trial of Mindfulness-Based Stress Reduction for Reducing Perceived Stress in Women Impacted by Large-Scale Disasters
ClinicalTrials.gov study NCT07283601. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Black Soldier Fly larvae (Hermetia illucens) meal is a viable protein source for Atlantic salmon (Salmo salar) during a large-scale controlled field trial under commercial-like conditions
GEO Series GSE241320. Salmo salar. 37 samples. Type: Expression profiling by high throughput sequencing.
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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.
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DANDI Archive for NWB datasets
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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.