Difference in GMT for HPV16 and HPV18 in PWH. by Alvine M. Akumbom (20460907)

“…GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges’s g -0.434 (95% CI: -0.823, -0.046) and Hedges’s g -0.57 (95% CI: -0.72, -0.43), respectively. …”

Fig 3 - by Alvine M. Akumbom (20460907)

“…GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges’s g -0.434 (95% CI: -0.823, -0.046) and Hedges’s g -0.57 (95% CI: -0.72, -0.43), respectively. …”

Summary of characteristics of studies reviewed. by Alvine M. Akumbom (20460907)

“…GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges’s g -0.434 (95% CI: -0.823, -0.046) and Hedges’s g -0.57 (95% CI: -0.72, -0.43), respectively. …”

Cumulative meta-analysis. by Alvine M. Akumbom (20460907)

“…GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges’s g -0.434 (95% CI: -0.823, -0.046) and Hedges’s g -0.57 (95% CI: -0.72, -0.43), respectively. …”

Summary of immunogenicity information. by Alvine M. Akumbom (20460907)

“…GMT results of HPV16 and HPV18 genotypes were significantly lower in PWH; Hedges’s g -0.434 (95% CI: -0.823, -0.046) and Hedges’s g -0.57 (95% CI: -0.72, -0.43), respectively. …”

Parameters of screws. by Pilan Jaipanya (12861176)

“…<div><p>Background</p><p>Lateral mass screw (LMS) is a more widely adopted method for posterior cervical spine fixation than the cervical pedicle screw (CPS). Despite its lower pullout strength, the insertions of LMS are more reproducible and have a lower risk. …”

Clinical characteristics of the study population. by Hun Gi Lee (21526538)

“…The total number of patients who met with P-TAs was 26,842, with a 43.1% reduction from 17,105–9,737. A decrease was observed across all age groups; however, the rate was lower in the geriatric and severely injured groups. …”

Effects of message content condition on outcomes. 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. …”

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. …”