FT-IR results. by Caglar Akcay (6910697)

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Trend analysis of the ν_s – RHOB in the range of data found in the dataset used for the optimized GPR. by Fahd Saeed Alakbari (10701871)

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Chemical analysis of the substrates before and after cultivation (see S3 in S2 File for reference). by Caglar Akcay (6910697)

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FT-IR results. by Caglar Akcay (6910697)

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The comparison of ν_s – DTc trends models with experimental measured values for RHOB = 2.02 g/cc and DTs =  265.03 us/ft. by Fahd Saeed Alakbari (10701871)

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(a) Taylor diagrams of Khandelwal et al. [13], Brabdas et al, Kumar et al. [12] models. (b) Taylor diagrams of Ranjbar-Karami et al. [14], Christaras et al. [52], Feng et al. [16],... by Fahd Saeed Alakbari (10701871)

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FT-IR results. by Caglar Akcay (6910697)

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(a, b). The statistical error analyses for the models using the same dataset. by Fahd Saeed Alakbari (10701871)

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FT-IR results. by Caglar Akcay (6910697)

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The comparison of ν_s – RHOB trends models with experimental measurements. by Fahd Saeed Alakbari (10701871)

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The comparison of ν_s – DTs trends models with experimental measured values for RHOB = 2.33 g/cc and DTc = 118.67 us/ft. by Fahd Saeed Alakbari (10701871)

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Distribution of continuous variables of all 3 visits (visit 1 = day 0, visit 2 = day 35, and visit 3 = day 70) of the PCSO-524 group and the placebo group. Results are shown as mea... by Nattapon Riengvirodkij (11268720)

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The optimized GPR approach’s cross-plotting for the training dataset. by Fahd Saeed Alakbari (10701871)

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Methodology flowchart. by Fahd Saeed Alakbari (10701871)

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The most common machine learning methods to predict ν_s. by Fahd Saeed Alakbari (10701871)

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Tricuspid regurgitation pressure gradient of all 17 dogs. by Nattapon Riengvirodkij (11268720)

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Trend analysis of the ν_s – DTc in the range found in the dataset used for the optimized GPR. by Fahd Saeed Alakbari (10701871)

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Statistical error analyses of the proposed or optimized GPR model. by Fahd Saeed Alakbari (10701871)

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FT-IR results. by Caglar Akcay (6910697)

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Density differences between pre- and post-measurements for program completers (N = 160). by Anton Kurapov (11346019)

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