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. …”

a Positive ion mode correlation heat map (A) Mild PTOA group VS Severe PTOA group (B) Mild PTOA group VS normal group (C) Severe PTOA group VS normal group. b. Negative ion mode co... by Peng-fei Han (694841)

Types of Bayesian spatiotemporal models. by Weiwei Meng (304234)

“…We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.…”

Ecological regression model fitting results. by Weiwei Meng (304234)

“…We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.…”

Correlation analysis. by Weiwei Meng (304234)

“…We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.…”

Scores of Burnout, Resilience, and PTS Over Time. by Rachel G. Baskin (22127334)

“…In addition, adequate protective equipment was found to be a predictor of lower pandemic stress.</p><p>Conclusions</p><p>Post-traumatic stress peaked in 2020 during lockdown in the United States and decreased significantly by 2022. …”

RM-ANOVA Post hoc Testing for PTS Across Time. by Rachel G. Baskin (22127334)

“…In addition, adequate protective equipment was found to be a predictor of lower pandemic stress.</p><p>Conclusions</p><p>Post-traumatic stress peaked in 2020 during lockdown in the United States and decreased significantly by 2022. …”

iBAT characterization of the <i>aP2-Drp1</i>^f/f neonatal mice. by Yuta Ibayashi (20404811)

Brain disintegration in <i>aP2- Drp1</i>^f/f neonatal mice. by Yuta Ibayashi (20404811)

LNd stimulate LPN to form a circadian feedback circuit. by Xin Yuan (174619)

Infection of CD 34 by Ancy Joseph (5634794)

“…Spleen weights at time of necropsy/death were significantly lower in HTLV-1-CTCF compared to HTLV-1-p12stop infected mice. …”

NPF-NPFR pathway in LNd-LPN feedback circuit fine-tune cooling induced locomotion increase. by Xin Yuan (174619)

The circadian LPN promote sleep through AstC pathway. by Xin Yuan (174619)

AC-LPN circuit control high temperature induced increase of evening sleep. by Xin Yuan (174619)