BMI versus change in soft tissue thickness in hydrated to dehydrated state. by Fatemeh Khorami (22041563)

Dataset. Dataset. by Michael R. Lawrence (21369854)

“…Serum levels of nerve growth factor (NGF), a biomarker of brain plasticity, were significantly lower in the long COVID group, which was significantly more likely than controls to have serum levels of inflammatory marker (interleukin (IL)-10) values greater than or equal to the median (p = 0.015). …”

Self-Report Questionnaires. by Michael R. Lawrence (21369854)

“…Serum levels of nerve growth factor (NGF), a biomarker of brain plasticity, were significantly lower in the long COVID group, which was significantly more likely than controls to have serum levels of inflammatory marker (interleukin (IL)-10) values greater than or equal to the median (p = 0.015). …”

Model selection based on best fit. by Angelina Mageni Lutambi (22097223)

“…The results showed that malaria incidence decreased with greater variance across Tanzania. Mean malaria incidence decreased from 0.347 (95% CI: 0.336, 0.357) in 2000 to 0.118 (95% CI: 0.114, 0.122) in 2020, relative to the increasing insecticide-treated bednets (ITNs) coverage (0.037; 95% CI: 0.036, 0.039 in 2000 to 0.496; 95% CI: 0.476, 0.517 in 2020). …”

Data Sheet 1_Disproportionate impact of the COVID-19 pandemic on socially vulnerable communities: the case of Jane and Finch in Toronto, Ontario.docx by Zahra Movahedi Nia (9238798)

“…The number of patients during the COVID-19 pandemic versus before that decreased significantly more for pop-smear tests (p = 0.041) and surgery waitlists (p = 0.037) for the Jane and Finch community.…”

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. …”

Results of the colorimetric MTT test. by Adela Klezlova (22608008)

“…In the study group, the IOP was statistically significantly lower by 29% at the end of the follow-up compared to the preoperative measurements (<i><i>p</i></i> = 0.009). …”

MO-SAM segmentation performance using the Grid method in arid/semi-arid landscape. by Qitong Wang (15279695)

Attitude towards NTDs in the study Area. by Uchechukwu M. Chukwuocha (6685790)

“…Quantitative data were analyzed using chi-square tests. Findings revealed a significant increase in NTDs awareness post-intervention (p < 0.05). …”

Dataset of results. by Uchechukwu M. Chukwuocha (6685790)

“…Quantitative data were analyzed using chi-square tests. Findings revealed a significant increase in NTDs awareness post-intervention (p < 0.05). …”

Respondents’ perception about the public artwork. by Uchechukwu M. Chukwuocha (6685790)

“…Quantitative data were analyzed using chi-square tests. Findings revealed a significant increase in NTDs awareness post-intervention (p < 0.05). …”

MO-SAM segmentation performance using the Grid method in the forested landscape. by Qitong Wang (15279695)

Parameters of screws. by Pilan Jaipanya (12861176)

“…For these reasons, surgeons may avoid CPS insertion despite its benefit of greater biomechanical strength. Therefore, an improvement in the CPS design is needed to avoid this catastrophic complication.…”

Variability of gait features during adaptation. by Samantha Jeffcoat (22783930)

Step length asymmetry and step width during split-belt adaptation. by Samantha Jeffcoat (22783930)

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)