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6,175 results for “Composite”
Database used to analyse body composition and physical fitness in children
<p>Descriptive characteristics for the entire sample and by age group, as well as differences between the<br>two age groups</p>
Alkyl lipid distribution, elemental composition and compound-specific 14C isotope composition in marine and terrestrial sedimentary archives from sub-Antarctic South Georgia
<p>The dataset comprises elemental data, alkyl lipid data and radiocarbon (14C) data that was obtained on sediment samples from sub-Antarctic South Georgia. The sediments were collected from a range of different sites, including lakes, peat deposits, a marine inlet and a fjord during RV Polarstern expedition PS81 in 2013. More details on the study sites, sampling and data evaluation can be found in Berg et al. (submitted manuscript to JGR Biogeochemistry).</p>
Small Variations in Ice Composition and Layer Thickness Explain Bright Reflections Below Martian Polar Cap Without Liquid Water
<p>These files include the model results used in Lalich et al. 2024 as well as the code necessary to analyze and reprooduce those results. See README for more detail. </p>
The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene
<p>Isotopic composition (deuterium and deuterium excess) of the French Illimani ice core drilled in 1999 with a revised dating detailed in the following manuscript:</p> <p>Françoise Vimeux and Amaëlle Landais, 2025. The isotopic composition of the French Illimani ice core in the Bolivian Andes supports the east-west South American precipitation dipole from the last deglaciation to the mid-Holocene. Quaternary Science Reviews 347, https://doi.org/10.1016/j.quascirev.2024.109098.</p>
Optimization of the thermomechanical behaviour of TRC composites
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Proximate and fiber composition of Commelina species
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Mechanisms of bimodal magmatism generation beneath Southwest Indian ridges: Implications for the variable composition of MORBs
<p><strong><span>Table S1. </span></strong><span>Chemical and isotopic compositions for lavas and scorias from the Southwest Indian ridge</span></p> <p><strong><span> </span></strong><strong><span>Table S2.<span> </span></span></strong><span>Major, trace, volatile element of glasses and melt inclusions from SWIR reported here.</span></p> <p><strong><span> </span></strong><strong><span>Table S3. </span></strong><span>Sr isotopes of glass, plagioclase, melt inclusion from SWIR, and glass and plagioclase standards</span></p> <p><strong><span> </span></strong><strong><span>Table S4. </span></strong><span>Major element compositions for olivine, spinel and plagioclase from the Southwest Indian ridge</span></p> <p><span> </span><strong><span>Table S5.<span> </span></span></strong>Volatile element of olivine and plagioclase from SWIR reported here</p> <p><span> </span><strong><span>Table S6.<span> </span></span></strong>Average value for volatile element of glasses and melt inclusions in SWIR compared to seawater.</p> <p><span> </span><strong><span>Table S7.<span> </span></span></strong>Helium concentrations and blank corrected isotopic ratios of glasses from Southwest Indian ridge reported here.</p> <p><strong><span> </span></strong><strong><span>Table S8.<span> </span></span></strong>Vesicle quantification and gas mass fraction in D30 lava and scoria samples.</p> <p><strong><span> </span></strong><strong><span>Table S9.<span> </span></span></strong><span>Modelling endmembers compositions of DMM, LCC and SCLM.</span></p>
Raw data for "Application of biological early warning systems in wastewater treatment plants: Introducing a promising approach to monitor changing wastewater composition"
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SI-B for "Application of biological early warning systems in wastewater treatment plants: Introducing a promising approach to monitor changing wastewater composition"
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Data from: Artificial light increases nighttime prevalence of predatory fishes, altering community composition on coral reefs
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Frost resistance of alkali-activated concrete with different compositions – parametric study
<p><span>Alkali-Activated Materials (AAM) are often considered to be very durable and also frost-resistant. However, there are also contrary experiences. This paper focuses on the frost resistance of AAMs of different compositions – different amounts of activator and different ratios between alkali (R<sub>2</sub>O) and silicon oxide content. Sodium water glass was used as the activator and its silicate modulus was modified by the addition of KOH. The R<sub>2</sub>O content was 4 -10 % and the R<sub>2</sub>O/SiO<sub>2</sub> weight ratio was 33/67 (water glass only) up to 100/0 (KOH only). The frost resistance index was tested at the ages of 28, 91 and 365 days. Specimens were cured in foil or water and comparative specimens were also stored in foil or water. </span><span>The results obtained are inconclusive. Firstly, when the reference specimens are stored in water, their bending strength decreases. This means that the frost resistance index is dependent on the use of the reference specimens – better results of frost resistance index are obtained for water-cured beams as reference specimens as they show lower strengths. The composition has a marginal effect on the frost resistance. Longer curing times also do not increase frost resistance.</span></p>
Dataset for "Predicting the Strength of Composites with Computer Vision Using Small Experimental Datasets"
<p>Composite_Strength_Prediction_by_CNN_v1.0</p>
Amphibole compositions record cold post-emplacement reequilibration in plutons
<h1>Amphibole compositions record cold post-emplacement reequilibration in plutons</h1> <p>Compiled and simulated data used in this study are included.</p> <h2>Description of the data and file structure</h2> <h3>ds01_Whole_Rock_and_Temperatures_Pressures_Equilibrium_Melt_Compositions_Higgins2021.csv.zip</h3> <p> Includes whole-rock compositional data for magmatic rocks (volcanic and intrusive) compiled from the GEOROC database and other published data, chemical compositional data for hornblende, and temperature, pressure, and equilibrium melt compositions calculated by the method in Higgins et al. (2021).</p> <h3><br>ds02_Whole_Rock_and_Temperatures_Putirka2016_Pressures_Ridolfi2022_Equilibrium_Melt_Compositions_Zhang2017.csv.zip</h3> <p> Includes whole-rock compositional data for magmatic rocks (volcanic and intrusive) compiled from the GEOROC database and other published data, chemical compositional data for hornblende, and temperature (Putirka2016), pressure (Ridolfi2022), and equilibrium melt compositions calculated by the method in Zhang et al. (2017).</p> <h3><br>ds03_Whole_Rock_Composition_and_Temperatures_Pressures_Derived_from_Biotite_LiandZhang.csv.zip</h3> <p> Includes whole-rock compositional data for magmatic rocks (volcanic and intrusive) compiled from the GEOROC database and other published data, chemical compositional data for biotite, and temperature and pressure calculated by the method in Li & Zhang (2022).</p> <h3><br>ds04_Simulation_Results_Using_Big_Dataset_as_Initial_Composition.csv.zip</h3> <p> Simulated dataset using whole-rock compositions of GEOROC arc magmatic rocks as initial compositions calculated by Perple_X, including melt, solid, and whole-rock chemical compositions.</p> <h2>Sharing/Access information</h2> <p>Data was derived from the following sources:</p> <p>* GEOROC: [https://georoc.mpch-mainz.gwdg.de//georoc/](https://georoc.mpch-mainz.gwdg.de//georoc/)</p> <h2>Code/Software</h2> <p>The code for analyzing the compiled data, calculating the geothermobarometer, and generating and analyzing the simulated data can be found here:[https://github.com/Geokeke/HornblendeReequilibration](https://github.com/Geokeke/HornblendeReequilibration)</p>
AlphaTrans: A Neuro-Symbolic Compositional Approach for Repository-Level Code Translation and Validation
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Wing with Root Holes - Hierarchical, random and bifurcation tiling with heterogeneity in micro-structures construction via functional composition.
<p>This microstructure has been created using tools and algorithms developed at the Technion, and are part of the IRIT geometric modeling kernel (<a href="https://www.cs.technion.ac.il/~irit/">https://www.cs.technion.ac.il/~irit/</a>).</p> <p>This specific wing is a functional composition of trivariate spline tiles inside a macro trivariate shape of a wing. The root tiles have through vertical holes in them.</p> <p>Model is provided in STL format.</p>
Data from: Temporal turnover of the soil microbiome composition is guild-specific
<p>Although spatial and temporal variation are both important components structuring microbial communities, the exact quantification of temporal turnover rates of fungi and bacteria has not been performed to date. In this study, we utilized repeated resampling of bacterial and fungal communities at specific locations across multiple years to describe their patterns and rates of temporal turnover. Our results show that microbial communities undergo temporal change at a rate of 0.010-0.025 per year (in units of Sorensen similarity), and the change in soil is slightly faster in fungi than in bacteria, with bacterial communities changing more rapidly in litter than soil. Importantly, temporal development differs across fungal guilds and bacterial phyla with different ecologies. While some microbial guilds show consistent responses across regional locations, others show site-specific development with weak general patterns. These results indicate that guild-level resolution is important for understanding microbial community assembly, dynamics and responses to environmental factors.</p>
Three dimensional microscale characterization of off-axis tunnelling cracks in non-crimp fabric based composites
<p>Video and x-ray data-sets behind the publications</p> <p>Bangaru, A.K., Mikkelsen, L.P. and, Sørensen, B.F. Three dimensional microscale characterization of off-axis tunnelling cracks in non-crimp fabric based composites, <em>Composites Science and Technology</em>, <strong>226</strong>, 109502, <a href="https://doi.org/10.1016/j.compscitech.2022.109502">https://doi.org/10.1016/j.compscitech.2022.109502</a>, 2022</p> <p>Videos: </p> <ul> <li>Figure 8: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig08_CrackBranching_v1.mpg">Fig08_CrackBranching_v1.mpg</a>, <a href="https://youtu.be/rrp8Ax1er5I">Youtube-link</a></li> <li>Figure 10a: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig10_a_MatrixPenetration.mpg">Fig10_a_MatrixPenetration.mpg</a>, <a href="https://video.dtu.dk/media/Fig10_a_MatrixPenetration.mpg/0_0ypbfkex">Video-link</a></li> <li>Figure 10b: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig10_b_MatrixPenetration_HighResolution.mpg">Fig10_b_MatrixPenetration_HighResolution.mpg</a>, <a href="https://video.dtu.dk/media/Fig10_b_MatrixPenetration_HighResolution/0_1bexfv16">Video-link</a></li> <li>Figure 10c: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig10_c_CrackTwisting_HighResolution.mpg">Fig10_c_CrackTwisting_HighResolution.mpg</a>, <a href="https://video.dtu.dk/media/Fig10_c_CrackTwisting_HighResolution/0_yphlldlh">Video-link</a></li> <li>Figure 14: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig14_CrackPenetration_HighResolution.mpg">Fig14_CrackPenetration_HighResolution.mpg</a>, <a href="https://youtu.be/MO0VBdyYlAw">Youtube-link</a></li> <li>Figure 15: <a href="https://zenodo.org/api/files/cb486bb8-8183-4b67-bb03-4ed5e48d6d31/Fig15_CrackDeflection_HighResolution.mpg">Fig15_CrackDeflection_HighResolution.mpg</a>, <a href="https://video.dtu.dk/media/Fig15_CrackDeflection_HighResolution/0_cqw7xgyg">Video-link</a></li> </ul> <p>Scan data:</p> <ul> <li>Fig08_SpecimenS1_DataSet.txm: Data behind figure 8</li> <li>Fig10_a_SpecimenS2_DataSet_LowResolution_Stitch22_FoV6.5.txm: Data behind figure 10a</li> <li>Fig10_b_c_SpecimenS2_DataSet_HighResolution_FoV1.5.txm: Data behind figures 10b, 10c, 11, and 13</li> <li>Fig14_SpecimenS2_DataSet_HighResolution_FoV1.5.txm: Data behind figure 14</li> <li>Fig15_SpecimenS3_DataSet_HIghResolution_FoV1.5.txm: Data behind figure 15</li> </ul> <p> </p> <p> </p>
Data from: Individual and interactive effects of chronic anthropogenic disturbance and rainfall on taxonomic, functional and phylogenetic composition and diversity of extrafloral nectary-bearing plants in Brazilian Caatinga
<p>Chronic anthropogenic disturbance (CAD) and climate change represent two of the major threats to biodiversity globally, but their combined effects are not well understood. Here we investigate the individual and interactive effects of increasing CAD and decreasing rainfall on the composition and taxonomic (TD), functional (FD) and phylogenetic diversity (PD) of plants possessing extrafloral nectaries (EFNs) in semi-arid Brazilian Caatinga. EFNs attract ants that protect plants against insect herbivore attack and are extremely prevalent in the Caatinga flora. EFN-bearing plants were censused along gradients of disturbance and rainfall in Catimbau National Park in north-eastern Brazil. We recorded a total of 2,243 individuals belonging to 21 species. Taxonomic and functional composition varied along the rainfall gradient, but not along the disturbance gradient. There was a significant interaction between increasing disturbance and decreasing rainfall, with CAD leading to decreased TD, FD and PD in the most arid areas, and to increased TD, FD and PD in the wettest areas. We found a strong phylogenetic signal in the EFN traits we analysed, which explains the strong matching between patterns of FD and PD along the environmental gradients. The interactive effects of disturbance and rainfall revealed by our study indicate that the decreased rainfall forecast for Caatinga under climate change will increase the sensitivity of EFN-bearing plants to anthropogenic disturbance. This has important implications for the availability of a key food resource, which would likely have cascading effects on higher trophic levels.</p>
Temperature and chemical composition of combustion gases over reaction time in several combustion tests conducted at a lab pilot plant to characterise a SRF prepared for an aluminium scrap pre-heating system (REVaMP project)
<p>Open access to experimental data generated by the REVaMP project (GA 869882, Horizon 2020, European Union) along the research of the combustion of a SRF, prepared from ASR, to be used as alternative fuel in a scrap pre-heater at an aluminium refinery plant.Research pertaining to Task 1.1 (WP1), Deliverable D1. <br> Underlying data for the publication Acha, E.; Lopez-Urionabarrenechea, A.;Delgado, C.; et al. Combustion of a Solid Recovered Fuel (SRF) Produced from the Polymeric Fraction of Automotive Shredder Residue (ASR). Polymers 2021, 13, 3807. https://doi.org/10.3390/polym13213807. Data related to Figures 3, 4, 5 in the article and Figures S3 and S5 of Supplementary materials of the manuscript.</p> <p>Subject: Study of the combustion of a SRF prepared from ASR in a lab-scale pilot plant consisting of a tank reactor and a packed-bed tubular reactor arranged in series, to evaluate the effects on kinetics and thermodynamics of the temperature and the type and flow rate of the oxidiser. Real-time measurements of the temperature of the tank, temperature of the gases and of the concentrations of O<sub>2</sub>, CO<sub>2</sub>, CO, N<sub>2</sub>O, NO<sub>2</sub>, NO, NH<sub>3</sub>, SO<sub>2</sub>, CH<sub>4</sub>, C<sub>2</sub>H<sub>6</sub>, C<sub>2</sub>H<sub>4</sub>, C<sub>3</sub>H<sub>8</sub>, C<sub>6</sub>H<sub>14</sub>, CH<sub>2</sub>O, HCl and HF in the combustion gases produced in 5 combustion runs performed at different reaction conditions. Useful information for designing the operation conditions of the SRF combustion chamber of the scrap pre-heater and for defining the flue gas cleaning requirements.</p>
FIGURE 3C. Composite areagram showing proposed terrane relationships within Sulawesi. 1 in Biotectonics of Sulawesi: Principles, methodology, and area relationships
FIGURE 3C. Composite areagram showing proposed terrane relationships within Sulawesi. 1 = Sula Spur, 2 = Palaeogene Clade.
ScienceDex guides
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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.