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89 results for “Test optimization”
GloMPO (Globally Managed Parallel Optimization) Benchmark Test Data
<p>Dataset associated with:<br> M. Freitas Gustavo and T. Verstraelen (2021), "GloMPO (Globally Managed Parallel Optimization) - a tool for expensive, black-box optimizations: application to ReaxFF reparameterizations".</p> <p>Contains optimization trajectories using the CMA-ES optimizer applied to various benchmark functions and ReaxFF reparameterizations. Compares optimization results using the GloMPO framework (github.com/mfgustavo/glompo) to unmanaged optimization results.</p>
Mutation-guided Metamorphic Testing of Optimality in AI Planning
<p>Experimental results presented in the article <em>Mutation-guided Metamorphic Testing of Optimality in AI Planning</em>, both the figures and the raw data.</p> <p> </p> <p>The framework itself is hosted on GitHub (see the link below).</p> <p>In order to use the data with the framework, unzip the files of the archive <em>results.zip</em> inside the folder <em>results/</em>.</p>
Test data set for macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins
<p>This a bundle of test data can be used to run the macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins.</p> <p>These data sets can be used to run the following macros that can be found on GitHub:</p> <ol> <li><a href="https://github.com/molcyto/MC-Ratio-96-wells">https://github.com/molcyto/MC-Ratio-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Ratio-Petri-dish">https://github.com/molcyto/MC-Ratio-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-Petri-dish">https://github.com/molcyto/MC-FLIM-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-Bleach-96-wells">https://github.com/molcyto/MC-Bleach-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Scatter5D">https://github.com/molcyto/MC-Scatter5D</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-96-wells">https://github.com/molcyto/MC-FLIM-96-wells</a></li> </ol> <p>Funding:<br> This work was supported by the NWO CW-Echo grant 711.011.018 (M.A.H. and T.W.J.G.), grant 12149 (T.W.J.G.) from the Foundation for Technological Sciences (STW) from the Netherlands</p> <p> </p>
Swab Testing to Optimize Pneumonia Treatment with Empiric Vancomycin
ClinicalTrials.gov study NCT06272994. IPD Sharing: YES. Countries: 1. Publications: 24.
Point-of-care Pharmacogenomic Testing to Optimize Isoniazid Dosing for Tuberculosis Prevention
ClinicalTrials.gov study NCT05413551. IPD Sharing: YES. Countries: 1. Publications: 1.
Multi-Objective Optimization of Load Test Designs
<p>Supplementary material for the paper: "Multi-Objective Optimization of Load Test Designs".</p> <p>Included in the supplementary material are the evaluation results and the proof and concept implementation.</p>
Optimizing Continuous Integration by Dynamic Test Selection
<p>Continuous integration (CI) is widely used in modern software engineering. However, it is an expensive practice. Some proposed approaches only focus on either intra- or inter-build cost reduction. In this paper, we propose an adaptive technique for dynamic test selection DTS, which combines intra- and inter-build cost reduction techniques. DTS uses build features to construct machine learning models to predict the probability of a specific build failure and transform the probability into the necessary test proportion, with respect to a selected test case prioritization technique. Based on the output of prediction model, it thus selects a prioritized test suite and a variable proportion of test cases with respect to a build. We constructed a large-scale dataset with approximately 115,000 builds, and conducted a controlled experiment using the dataset. The experiment shows that DTS outperforms existing techniques significantly. It detects 19.9% to 32.5% more failed test cases, compared with state-of-the-art techniques evaluated in the experiment. At the same time, DTS performs better than all three existing peer techniques on approximately 47% of projects. Moreover, the experiment also shows that our failure prediction model has an improvement of 0.15 in Area Under Curve (AUC), compared to prior machine learning models.</p>
Data for: Nest material preferences in wild hazel dormice Muscardinus avellanarius: Testing predictions from optimal foraging theory
<p class="MsoNormal">Obtaining nesting material presents an optimal foraging problem, collection of materials incurs a cost in terms of risk of predation and energy spent, and individuals must balance these costs with the benefits of using that material in the nest. The hazel dormouse, <em>Muscardinus avellanarius</em> is an endangered British mammal in which both sexes build nests. However, whether material used in their construction follows the predictions of optimal foraging theory is unknown. Here, we analyse the use of nesting materials in forty two breeding nests from six locations in Southwest England. Nests were characterised in terms of which plants were used, the relative amount of each plant, and how far away the nearest source was. We find that dormice exhibit a preference for plants closer to the nest, but that the distance they are prepared to travel depends on the plant species. Dormice travelled further to collect honeysuckle <em>Lonicera periclymenum</em>, oak <em>Quercus robur</em>, and beech <em>Fagus sylvatica</em> than any other plants. Distance did not affect the relative amount used, although the proportion of honeysuckle in nests was highest, and more effort was expended collecting honeysuckle, beech, bramble <em>Rubus fruticosus</em> and oak compared to other plants. Our results suggest that not all aspects of optimal foraging theory apply to nest material collection. However, optimal foraging theory is a useful model to examine nest material collection, providing testable predictions. As found previously honeysuckle is important as a nesting material, and should be taken account when assessing suitability of sites for dormice.</p>
Clinical Validation of An Optimized Multi-Target Stool DNA (Mt-sDNA 2.0) Test, for Colorectal Cancer Screening "BLUE-C"
ClinicalTrials.gov study NCT04144738. IPD Sharing: YES. Countries: 1. Publications: 3.
A New APPROACH to HIV Testing: Adaptation of POCT for Pharmacies to Reduce Risk and Optimize Access to Care in HIV
ClinicalTrials.gov study NCT03210701. IPD Sharing: NO. Countries: 1. Publications: 2.
Optimization of a New Adaptive Intervention to Increase COVID-19 Testing
ClinicalTrials.gov study NCT04757298. IPD Sharing: YES. Countries: 1. Publications: 3.
Using MOST to Optimize an Intervention to Increase COVID-19 Testing for Frontline Essential Workers
ClinicalTrials.gov study NCT05139927. IPD Sharing: NO. Countries: 1. Publications: 1.
Factorial Trial Testing Guided Thinking Tasks to Optimize a Physical Activity Intervention
ClinicalTrials.gov study NCT05235360. IPD Sharing: YES. Countries: 1. Publications: 1.
Medication Optimization Using Pharmacogenetic Testing and the G-DIG to Reduce Polypharmacy in a Mental Health Population
ClinicalTrials.gov study NCT03468309. IPD Sharing: NO. Countries: 1. Publications: 1.
Data from: Testing the optimal defense hypothesis in nature: variation for glucosinolate profiles within plants
Open the record for dataset details and reuse information.
Optimal test-assisted quarantine strategies for COVID-19
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Data for: Nest material preferences in wild hazel dormice Muscardinus avellanarius: Testing predictions from optimal foraging theory
Open the record for dataset details and reuse information.
Data for: Combining radio-telemetry and radar measurements to test optimal foraging in an aerial insectivore bird
Open the record for dataset details and reuse information.
Images of loop-mediated isothermal amplification (LAMP) for SARS-CoV-2 testing and optimized 'Cap-iLAMP'
<p>Here we present images of loop-mediated isothermal amplification (LAMP) and optimized Cap-iLAMP (capture and improved loop-mediated isothermal amplification). Cap-iLAMP combines a hybridization capture-based RNA extraction of gargle lavage samples with an improved colorimetric RT-LAMP assay and smartphone-based color scoring. Cap-iLAMP is compatible with point-of-care testing and enables the detection of SARS-CoV-2 positive samples in less than one hour. The sensitivity is 97% and the specificity is 99%.</p>
Data from: Context-dependence of maternal effects: testing assumptions of optimal egg size, differential- and sex-allocation models
If offspring develop in adverse conditions, the maternal component of their phenotypic variation might increase due to the stronger dependence of offspring traits on parental investment. This should result in increased parental investment to individual offspring, as assumed by the model of optimal egg size. The opposite pattern, i.e., stronger dependence of offspring fitness on parental investment and consequently larger parental investment under good conditions is assumed by both the theory of differential allocation if attractive males provide material benefits, and reproductive compensation if they invest less into paternal care. Another influential idea is the Trivers-Willard model, which assumes sex-specific dependence of offspring fitness on parental investment. Here we tested these ideas by examining the effects of egg size on offspring fitness across many postnatal contexts in the Collared Flycatcher Ficedula albicollis. We employed a cross-fostering design that generated variation in egg size within nests and used brood means of fledgling mass as a functional measure of the quality of rearing conditions. Effects of egg size on three offspring traits, including lifetime reproductive success of recruits, were more pronounced in low-quality broods. These results support the assumption of the model of optimal egg size. Based on female preference for males providing material benefits, this pattern could support differential allocation, if attractive males invest less in paternal care, or reproductive compensation, if they invest more. By comparison, we did not find any evidence for sex specificity of fitness returns that might explain sex monomorphism of egg size in this species. The challenge for future studies will be the integration of components of parental investment and offspring fitness into their global measures and testing how the former affects the latter across gradients of postnatal conditions.
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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.
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.