GMT by age cohort for PWH and PWoH. by Alvine M. Akumbom (20460907)

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

Fig 4 - by Alvine M. Akumbom (20460907)

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

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

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

Fig 3 - by Alvine M. Akumbom (20460907)

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

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

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

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

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

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

“…A random effects meta-analysis was performed comparing geometric mean titer (GMT) in PWH to PWoH. Twenty-eight studies out of 988 were eligible for inclusion in our study, and qualitatively synthesized. …”

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. …”

PLE prevents the development of psoriasis by inhibiting the activation of TLR4/NF- κB and PI3K/AKT signaling pathway. by Xiaoqiang Huang (1457860)

AO/EtBr Staining of Cancer cell lines: <i>To check whether vitamin D3 promoted cell death in cancer cells, a dual staining protocol was implemented as detailed in the methods secti... by Vidya G. Bettada (22208808)

Spontaneous oxycodone withdrawal transiently eliminates diurnal changes in NREM depth. by Michael Gulledge (20577135)

Myeloid knockout <i>VANGL2</i> exacerbates the progression of DSS-induced colitis in mice. by Huaji Jiang (16907514)

Down-regulation of VANGL2 in IBD patients triggers overt activation of NLRP3 inflammasome. by Huaji Jiang (16907514)

Definitions of the key terms used in this study. by Eriko Takahashi (22608061)

“…Participants (N = 577, mean age = 25.1 years, SD = 5.1) were recruited from an online community. …”

Spontaneous oxycodone withdrawal disrupts sleep/wake architecture. by Michael Gulledge (20577135)

“…For lights on, when rats show less % time asleep, the number of NREM (<b>B, left panel</b>) and Wake (<b>D, left panel</b>) bouts is increased, with corresponding decreases in NREM and REM bout duration. For lights off, there is a significant increase in the # of bouts of all sleep stages (<b>B, C, D, right panels</b>) with a corresponding decrease in Wake bout duration (<b>D, right panel</b>). …”

Gating strategy of experiment using 30 min EdU pulses experiments in mOr2-Piwi1 juvenile polyps. by Eudald Pascual-Carreras (12115380)