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59 results for “Material optimization”
Optimization of the Dosage of Chopped Basalt Fibers in Asphalt Pavement Surface Course Materials for Semi-rigid Base with Functional Requirements
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Repeatability materials for paper "Database-Inspired Optimizations for Statistical Analysis"
<p>This repository contains files to replicate experiments in our paper "Database-Inspired Optimizations for Statistical Analysis", in particular data derived from the American Community Survey (ACS). Experiment scripts to use these files are here: https://scm.cwi.nl/DA/raaql-paper-experiments</p>
Performance Advancements in P-Type TaFeSb-Based Thermoelectric Materials through Composition and Composite Optimizations
<p>The full data sets for the manuscript "Performance Advancements in P-Type TaFeSb-Based Thermoelectric Materials through Composition and Composite Optimizations" by Naderloo, et al.</p> <p>The paper is published in Energy & Environmental Science: <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D4EE04819A">https://doi.org/10.1039/D4EE04819A</a></p>
Supplemental materials for: Peri- and post-pubertal estrogen exposures of female mice optimize uterine responses later in life
<p>At birth, all female mice, including those that either lack estrogen receptor α (ERα-knockout) or that express mutated forms of ERα (AF2ERKI), have a hypoplastic uterus. However, uterine growth and development that normally accompanies pubertal maturation does not occur in ERα-knockout or AF2ERKI mice, indicating ERα mediated estrogen signaling is essential for this process. Mice that lack Cyp19 (aromatase, ArKO mice), an enzyme critical for estrogen (E2) synthesis, are unable to make E2, and lack pubertal uterine development. A single injection of E2 into ovariectomized adult (10 weeks old) females normally results in uterine epithelial cell proliferation, however, we observe that, although ERα is present in the ArKO uterine cells, no proliferative response is seen. We assessed the impact of exposing ArKO mice to E2 during pubertal and post-pubertal windows and observed that E2 exposed ArKO mice acquired growth responsiveness. Analysis of differential gene expression between unexposed ArKO samples and samples from animals exhibiting the ability to mount an E2-induced uterine growth response (WT or E2 exposed ArKO) revealed activation of EZH2 and HAND2 signaling and inhibition of GLI1 responses. EZH2 and HAND2 are known inhibit uterine growth, and GLI1 is involved in IHH signaling, which is a positive mediator of uterine response. Finally, we show that exposure of ArKO females to dietary phytoestrogens results in their acquisition of uterine growth competence. Altogether our findings suggest that pubertal levels of endogenous and exogenous estrogens impact biological function of uterine cells later in life via ERα-dependent mechanisms.</p>
Data from: Quantification and optimization of ADF-STEM image contrast for beam sensitive materials
Many functional materials are difficult to analyze by Scanning Transmission Electron Microscopy (STEM) on account of their beam sensitivity and low contrast between different phases. The problem becomes even more severe when thick specimens need to be investigated, a situation that is common for materials that are ordered from the nanometer to micrometer length scales or when performing dynamic experiments in a TEM liquid cell. Here we report a method to optimize annular dark-field (ADF) STEM imaging conditions and detector geometries for thick and beam-sensitive low-contrast specimen using the example of a carbon nanotube/polymer nanocomposite. We carried-out Monte Carlo simulations as well as quantitative ADF-STEM imaging experiments to predict and verify optimum contrast conditions. The presented method is general, can be easily adapted to other beam-sensitive and/or low-contrast materials, as shown for a polymer vesicle within a TEM liquid-cell, and can act as an expert guide on whether an experiment is feasible and to determine the best imaging conditions.
Supplementary Materials for "Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization"
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Supplementary material 1 from: Bylemans J, Gleeson DM, Lintermans M, Hardy CM, Beitzel M, Gilligan DM, Furlan EM (2018) Monitoring riverine fish communities through eDNA metabarcoding: determining optimal sampling strategies along an altitudinal and biodiversity gradient. Metabarcoding and Metagenomics 2: e30457. https://doi.org/10.3897/mbmg.2.30457
: Data type: Microsoft Word Document (.docx)
Supplementary material 2 from: Bylemans J, Gleeson DM, Lintermans M, Hardy CM, Beitzel M, Gilligan DM, Furlan EM (2018) Monitoring riverine fish communities through eDNA metabarcoding: determining optimal sampling strategies along an altitudinal and biodiversity gradient. Metabarcoding and Metagenomics 2: e30457. https://doi.org/10.3897/mbmg.2.30457
: Data type: statistical data
Materials Science Optimization Benchmark Dataset for Multi-fidelity Hard-sphere Packing Simulations
Benchmarks are an essential driver of progress in scientific disciplines. Ideal benchmarks mimic real-world tasks as closely as possible, where insufficient difficulty or applicability can stunt growth in the field. Benchmarks should also have sufficiently low computational overhead to promote accessibility and repeatability. The goal is then to win a "Turing test" of sorts by creating a surrogate model that is indistinguishable from the ground truth observation (at least within the dataset bounds that were explored), necessitating a large amount of data. In the fields of materials science and chemistry, industry-relevant optimization tasks are often hierarchical, noisy, multi-fidelity, multi-objective, high-dimensional, and non-linearly correlated while exhibiting mixed numerical and categorical variables subject to linear and non-linear constraints. To complicate matters, unexpected, failed simulation or experimental regions may be present in the search space. In this study, 438371 random hard-sphere packing simulations representing 279 CPU days worth of computational overhead were performed across nine input parameters with linear constraints and two discrete fidelities each with continuous fidelity parameters and results were logged to a free-tier shared MongoDB Atlas database. Two core tabular datasets resulted from this study: 1. a failure probability dataset containing unique input parameter sets and the estimated probabilities that the simulation will fail at each of the two steps, and 2. a regression dataset mapping input parameter sets (including repeats) to particle packing fractions and computational runtimes for each of the two steps. These two datasets can be used to create a surrogate model as close as possible to running the actual simulations by incorporating simulation failure and heteroskedastic noise. For the regression dataset, percentile ranks were computed within each of the groups of identical parameter sets to enable capturing heteroskedastic noise. This is in contrast with a more traditional approach that imposes a-priori assumptions such as Gaussian noise e.g., by providing a mean and standard deviation. A similar approach can be applied to other benchmark datasets to bridge the gap between optimization benchmarks with low computational overhead and realistically complex, real-world optimization scenarios.
Supplemental materials for: Peri- and post-pubertal estrogen exposures of female mice optimize uterine responses later in life
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Data from: Quantification and optimization of ADF-STEM image contrast for beam sensitive materials
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Automated array-CGH optimized for archival formalin-fixed, paraffin-embedded tumor material
GEO Series GSE7122. Homo sapiens. 39 samples. Type: Genome variation profiling by genome tiling array.
Multi-objective Optimization of Long-run Average and Total Rewards: Supplemental Material
<p>Supplemental Material for the Paper:<br> Multi-objective Optimization of Long-run Average and Total Rewards<br> by Tim Quatmann and Joost-Pieter Katoen.</p> <p>This artifact contains our implementation for the paper "Multi-objective Optimization of Long-run Average and Total Rewards". The implementation is fully integrated into the model checker <a href="http://stormchecker.org">Storm</a>.<br> We include the sources and dependencies of Storm as well as the related tools <a href="http://qav.cs.ox.ac.uk/multigain">MultiGain</a> and <a href="http://www.prismmodelchecker.org/games">PRISM-games</a>.<br> Moreover, we include model files and scripts for replicating *all* experiments as conducted for the paper.<br> The original logfiles obtained during our experiments are included as well.</p> <p>The artifact has been tested to work with the <a href="https://zenodo.org/record/4041464">TACAS 21 Artifact Evaluation VM</a> running Ubuntu 20.04 LTS</p>
Supplementary material to `Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5'
<p>This repository contains the supplementary material to the following paper: Hoffmann, L., Haghighi Mood, K., Herten, A., Hrywniak, M., Kraus, J., Clemens, J., and Liu, M., Accelerating Lagrangian transport simulations on graphics processing units: performance optimizations of MPTRAC v2.5, Geoscientific Model Development, submitted, 2023.</p><p> </p>
Supplementary material for the article entitled "Socioeconomic Analysis of the Proposed Opening of the Brazilian energy Market Through the Combination of Forecast Method with the Optimized Tariff Model"
<p>This supplementary material includes the input data used for the simulations conducted in the article.</p>
A Comparison Between Protemp and Flowable Light Cure Composite Material for Creating Optimal Gingival Emergence Profile Around Implant
ClinicalTrials.gov study NCT07196293. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Optimization of DE-CTPA Images and Diagnostic Pathway: Using Low Concentration Iodine Contrast Material
ClinicalTrials.gov study NCT06212882. IPD Sharing: YES. Countries: 1. Publications: 0.
Optimizing Non-surgical Endodontic Retreatment: A 3D CBCT Quantification of Root Canal Bioceramic Filling Material Removal
<div> <div> <div> <p>AVAILABILITY OF DATA </p> </div> </div> </div>
Supplementary Materials for "Surrogate-based Automated Hyperparameter Optimization for Expensive Automotive Crashworthiness Optimization"
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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.