Participant characteristics, N = 502. by Rhyan N. Vereen (10765678)

“…</p><p>Results</p><p>The CI campaign had significantly higher perceived cultural relevance (M = 4.61) than the general audience (M = 3.64) or control (M = 3.66; p’s<0.05) campaigns. …”

Sample of study stimuli by content condition. by Rhyan N. Vereen (10765678)

“…</p><p>Results</p><p>The CI campaign had significantly higher perceived cultural relevance (M = 4.61) than the general audience (M = 3.64) or control (M = 3.66; p’s<0.05) campaigns. …”

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. …”

Flow diagram of participants selection. by Wei Huang (36889)

“…Multivariable logistic regression evaluated associations between BRI and LMM, while multivariable linear regression assessed relationships between BRI and appendicular skeletal muscle mass (ASM)/BMI. …”

Minimal data set. by Wei Huang (36889)

“…Multivariable logistic regression evaluated associations between BRI and LMM, while multivariable linear regression assessed relationships between BRI and appendicular skeletal muscle mass (ASM)/BMI. …”

Weighted comparison of baseline characteristics. by Wei Huang (36889)

“…Multivariable logistic regression evaluated associations between BRI and LMM, while multivariable linear regression assessed relationships between BRI and appendicular skeletal muscle mass (ASM)/BMI. …”

Raw data_clean. by Carlos Sepúlveda (15272797)

“…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …”

Experimental design. by Carlos Sepúlveda (15272797)

“…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …”

Characterization of the participants. by Carlos Sepúlveda (15272797)

“…Conversely, being overweight or obese is associated with lower CRF, which can lead to decreased daily energy expenditure and reduced physical activity. …”

<i>Aedes aegypti</i> database from SAGO traps. by Jesús A. Aguilar-Durán (9931967)

“…Nonetheless, further research is needed to verify and validate their effectiveness at larger operational scales.</p></div>…”

Changes in alpha diversity in the weeks before anti-TNF-a treatment. by Katrine Carlsen (5477300)

“…The analysis found a significant association across all subjects for Shannon diversity with decreasing diversity in the lead up to the next treatment (lmer model, beta = -0.018, <i>p</i> = 0.036) and no association for observed diversity (<i>p</i>>0.1). …”

Characteristics of children in the study. by Shijie Yu (511369)

“…The self-evaluation of eye health was positively associated with both UI values and VAS scores. Furthermore, decreases in UI values and VAS scores were associated to the onset of myopia, and were more pronounced in children with myopia progression.…”

Methylation detection in the rDNA 28S gene body by MSP is robust and sensitive to methylation state of specific sites. by Stephen Flint Smith (22614954)

Gas-Phase Molecular Structure of 1‑Chlorosilatrane: Electron Diffraction Study and Assignment of Photoelectron Spectrum by Elena F. Belogolova (2025418)

“…This result shows that the Si←N bond length in 1-halosilatranes decreases when the halogen is replaced by an atom that forms a weaker bond with Si, rather than by a more electronegative atom. …”

Gas-Phase Molecular Structure of 1‑Chlorosilatrane: Electron Diffraction Study and Assignment of Photoelectron Spectrum by Elena F. Belogolova (2025418)

“…This result shows that the Si←N bond length in 1-halosilatranes decreases when the halogen is replaced by an atom that forms a weaker bond with Si, rather than by a more electronegative atom. …”

Effect of high percentage spliced in titin truncating variant on minimum LVEF stratified by genetic similarity to 1000 Genomes Project reference population excluding those with isc... by John DePaolo (17290776)