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A COSMIC-2-Based Global Mean TEC Model and Its Application to Calibrating IRI-2020 Global Ionospheric Maps
Published 2025-07-01Get full text
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Simulation of the African ITCZ during austral summer seasons and ENSO phases: application of an RCM derived from stretched grid ESM
Published 2025-07-01“…It also provides great potential for climate applications with suitable bias corrections techniques, albeit the source and mechanism of its dynamic error growth deserve further investigation.…”
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Optimised block bootstrap: an efficient variant of circular block bootstrap method with application to South African economic time series data
Published 2024-10-01“…Results demonstrated that OBB consistently outperformd circular block bootstrap (CBB), providing more accurate forecasts with lower root mean square error (RMSE), which assessed variance, and lower mean absolute error (MAE), which measured bias, across various time series models and parameter settings. …”
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APPLICATION OF TOTAL-REFLECTION X-RAY FLUORESCENCE SPECTROMETRY (TXRF) TO GEOLOGICAL OBJECTS: EXPERIENCE OF THE TXRF LABORATORY, CENTER FOR GEODYNAMICS AND GEOCHRONOLOGY
Published 2022-06-01“…Special attention has been paid to the sample preparation procedure because it is one of the main sources of errors in the analysis. Preparing thin homogeneous specimen from the solid sample with a complex mineral matrix is not easy. …”
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The Signification (Referent) of the Qur'an in the Process of Presenting Hadith; Based on the Application of the Supply Criterion (Standard) by the Infallibles (Maʿṣūmīn) (p.b.u.t.)...
Published 2020-09-01“…Forgery (invention) of hadith, error and mistake of some narrators in hearing, understanding or quoting hadith indicates the necessity of criticizing narrations to ensure their correctness or incorrectness. …”
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Machine learning application to predict binding affinity between peptide containing non-canonical amino acids and HLA-A0201.
Published 2025-01-01“…Our model demonstrates robust performance, with 5-fold cross-validation yielding an R2 value of 0.477 and a root-mean-square error (RMSE) of 0.735, indicating strong predictive capability for peptides with NCAAs. …”
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