Amplitude for A/L = 0.02. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Graph for maximum Frequency at G_y = 0. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Graph for maximum Power at G_y = 0. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Amplitude for A/L = 0.03. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Summary of experimentation results. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Piezoelectric eel. by Muhammad Hammad Bucha (21736111)

“…Increased surface roughness significantly reduced power output, flapping frequency, and amplitude. …”

Interaction panel of Treat × Period effect (T × P) for ether extract intake (g/d) as influenced by feeding pasteurized waste milk (WM) or milk replacer (MR) to newborn Holstein cal... by Shahryar Kargar (18880600)

Interaction panel of Treat × Period effect (T × P) for body measurements as influenced by feeding pasteurized waste milk (WM) or milk replacer (MR) to newborn Holstein calves (n =... by Shahryar Kargar (18880600)

Interaction panel of Treat × Period effect (T × P) for eating time (min/8-h) and sorting index (%) on sieve 2.36 mm and bottom pan as influenced by feeding pasteurized waste milk (... by Shahryar Kargar (18880600)

Interaction panel of Treat × Period effect (T × P) for starter intake (g/d), body weight (kg), average daily gain (g/d), and feed efficiency (g/g) as influenced by feeding pasteuri... by Shahryar Kargar (18880600)

<b>Data for s</b><b>easonal variations in coral lipids and their significance for energy maintenance in the </b><b>South China Sea</b> by Hongyan Mo (19721569)

“…<p dir="ltr">In recent years, the intensification of global warming and extreme climate have led to an increase in the frequency and severity of coral bleaching. Coral bleaching means a decrease in symbiotic zooxanthellae density (ZD). …”

IL-10 levels in tumor lysates post-treatment. by Hedieh Zargaran (21410233)

Clustering analysis of total and active RNAP II at genes during the transition from G1 to G2. by Douglas Maya-Miles (7024967)

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Effect of <i>slc43a3</i> deletion on metabolic performance parameters in male and female WT and KO mice. by Aaron L. Sayler (19797446)

Effect of <i>slc43a3</i> deletion on the diurnal cycle of oxygen consumption (VO₂) in male and female mice. by Aaron L. Sayler (19797446)