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Showing 1,501 - 1,520 results of 4,397 for search '(compositional OR composition) variability', query time: 0.19s Refine Results
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    The Effect of Nano-B4C Additive on Microstructure and Mechanical Properties of Pressureless Sintering SiC Bodies by Behnam Kozekanan, Alireza Moradkhani, Hamidreza Baharvandi, Valiollah Panahizadeh

    Published 2023-04-01
    “…In this study, the mechanical properties, microstructure, and fracture behavior of SiC-NanoB4C composites have been investigated with different weight percentages of secondary phase including 0, 0.25, 0.5, 0.75, 1, 2, and 3 wt.% nanoB4C produced by pressureless sintering. …”
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  7. 1507

    Improving Mechanical Properties of Nanocomposite-based Epoxy by High-impact Polystyrene and Multiwalled Carbon Nanotubes: Optimizing by a Mixture Design Approach by Yasser Rostamiyan

    Published 2017-04-01
    “…In the current study the influence of weight percentage of HIPS, weight percentage of CNT and hardener content on damping 1st and damping 2nd properties of epoxy/HIPS/CNT hybrid composite wase valuated. Mixture design methodology was employed to generate mathematical models for predicting damping 1st and damping 2nd behaviors of new mentioned hybrid nanocomposite as function of physical factors and optimizing desired mechanical properties. …”
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    Decomposition analysis of disparities in infant mortality rates across 27 US states by Benjamin Sosnaud

    Published 2024-05-01
    “…CONTRIBUTION: Decomposing cross-state differences in IMRs reveals considerable heterogeneity in the contribution of sociodemographic composition. This highlights variability in the social processes that produce disparities in infant mortality across populations. …”
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  14. 1514

    Characterization of Spent Grain from Irish Whiskey Distilleries for Biorefinery Feedstock Potential to Produce High-Value Chemicals and Biopolymers by Rasaq S. Abolore, Dileswar Pradhan, Swarna Jaiswal, Amit K. Jaiswal

    Published 2024-12-01
    “…This compositional variability highlights the importance of understanding DSG’s structural properties to optimize its use as a lignocellulosic biomass feedstock. …”
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  15. 1515

    Ranges of B, Cd, Cr, Cu, Fe, Pb, Sr, Tl, and Zn Concentrations and Isotope Ratios in Environmental Matrices from an Urban Area by Nicola Pallavicini, Emma Engström, Douglas C. Baxter, Björn Öhlander, Johan Ingri, Scott Hawley, Catherine Hirst, Katerina Rodushkina, Ilia Rodushkin

    Published 2018-01-01
    “…Further implementation of isotopic techniques in natural sciences requires a better understanding of the range of elemental and isotopic compositional variability in environmental matrices. …”
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  16. 1516

    Continual Day–Night eDNA Detectability Amidst Diel Reef Species Fluctuations on Diver Transects by Katrina M. West, Tyson R. Jones, Lara Denis‐Roy, Olivia J. Johnson, Ella Clausius, Graham Edgar, Bruce Deagle

    Published 2024-09-01
    “…Given high eDNA sample variability, however, we recommend a high replication level (> 10 × 1 L samples) to produce robust site community composition profiles. …”
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  17. 1517

    Significant Serpents: Predictive Modelling of Bioclimatic Venom Variation in Russell's Viper. by Navaneel Sarangi, R R Senji Laxme, Kartik Sunagar

    Published 2025-04-01
    “…Our models effectively captured regional differences in venom composition and linked climatic conditions with functional variations.…”
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  18. 1518

    Crystal Chemistry and Genetic Implications of Pink Tourmalines from Distinct Pegmatite Provinces by Floriana Rizzo, Ferdinando Bosi, Gioacchino Tempesta, Federica Iommazzo, Giovanna Agrosì

    Published 2025-04-01
    “…Tourmalines show a wide compositional variability, with pink tourmalines being particularly prized as gemstones. …”
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  19. 1519

    Modeling the Higher Heating Value of Spanish Biomass via Neural Networks and Analytical Equations by Anbarasan Jayapal, Fernando Ordonez Morales, Muhammad Ishtiaq, Se Yun Kim, Nagireddy Gari Subba Reddy

    Published 2025-07-01
    “…The optimized ANN achieved strong predictive accuracy (validation R<sup>2</sup> ≈ 0.81; mean squared error ≈ 1.33 MJ/kg; MAE ≈ 0.77 MJ/kg), representing a substantial improvement over 54 analytical models despite the known complexity and variability of biomass composition. Importantly, in direct comparisons it significantly outperformed 54 published analytical HHV correlations—the ANN achieved substantially higher R<sup>2</sup> and lower prediction error than any fixed-form formula in the literature. …”
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  20. 1520

    Pollen holographic images and light-induced fluorescence measurements at the species level by Sophie Erb, Alexis Berne, Bernard Clot, Maria Lbadaoui-Darvas, Gian-Duri Lieberherr, Marie-Pierre Meurville, Fiona Tummon, Benoît Crouzy

    Published 2025-05-01
    “…Their potential reuse can also be to study pollen morphological and compositional variability at the species level.…”
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