Showing 241 - 260 results of 12,904 for search '(( significantly increased decrease ) OR ( significant ((bins decrease) OR (nn decrease)) ))*', query time: 0.59s Refine Results
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    <b>Nest mass in forest tits </b><b><i>Paridae</i></b><b> </b><b>increases with elevation and decreasing body mass, promoting reproductive success</b> by Clara Wild (19246606)

    Published 2025
    “…We found that nest mass increased by ~ 60% along the elevational gradient, but the effect of canopy openness on nest mass was not significant, while nest mass decreased along the ranked species from the smallest <i>Periparus ater</i> to the medium-sized <i>Cyanistes caeruleus</i> and the largest <i>Parus major</i>. …”
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    Evaluation results. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
  14. 254

    Dataset with steel insert. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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    Reference dataset. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
  16. 256

    Dataset with aluminium insert. by Briya Tariq (19666901)

    Published 2024
    “…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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    R project including metadata update. by Frederik Stein (22146203)

    Published 2025
    “…<div><p>The increasing number of Barcode of Life Database (BOLD) records per species and genus leads to contradictory species assignments within Barcode Index Numbers (BINs), serving as identifiers for the BOLD ID engine. …”