Model calculation diagram. by Ming Zhang (9736)

“…When the height is 2.5m and above, the windbreak efficiency is greater than 90%, and the windbreak effect is significantly improved. (2) The change of sand barrier height has a significant effect on the windbreak efficiency between the second and third sand barriers. (3) Among the three sand-blocking fences, when the height of the sand-blocking fence is 2.5m, the thickness of the sand is 50.51% and 58.33% higher than that of the 2m high sand-blocking fence, and the sand-blocking effect is the most significant. …”

Grid independence verification. by Ming Zhang (9736)

“…When the height is 2.5m and above, the windbreak efficiency is greater than 90%, and the windbreak effect is significantly improved. (2) The change of sand barrier height has a significant effect on the windbreak efficiency between the second and third sand barriers. (3) Among the three sand-blocking fences, when the height of the sand-blocking fence is 2.5m, the thickness of the sand is 50.51% and 58.33% higher than that of the 2m high sand-blocking fence, and the sand-blocking effect is the most significant. …”

Descriptive statistics. by Yintu Bao (12113769)

“…The analysis reveals that the SHRR program significantly reduces travel frequency, likely due to improved local accessibility that decreases the need for frequent trips. …”

Variable description. by Yintu Bao (12113769)

“…The analysis reveals that the SHRR program significantly reduces travel frequency, likely due to improved local accessibility that decreases the need for frequent trips. …”

Village characteristics. by Yintu Bao (12113769)

“…The analysis reveals that the SHRR program significantly reduces travel frequency, likely due to improved local accessibility that decreases the need for frequent trips. …”

Research data 2. by Yintu Bao (12113769)

“…The analysis reveals that the SHRR program significantly reduces travel frequency, likely due to improved local accessibility that decreases the need for frequent trips. …”

Experimental procedures. by Ellen Chan (22177558)

“…</p><p>Results</p><p>Two-way repeated measures analysis of covariance (ANCOVA) was adopted to minimize the confounding effect from covariates identified (maximal tolerable gait speed for EMG amplitude analysis, and gender for pain intensity and performance in lumbar movement control (LMC) tests). Significant post-training improvement in pain intensity (p = 0.014) and overall performance of the LMC tests (p = 0.006) were found for those who received backward walking training. …”

Experimental procedures. by Ellen Chan (22177558)

“…</p><p>Results</p><p>Two-way repeated measures analysis of covariance (ANCOVA) was adopted to minimize the confounding effect from covariates identified (maximal tolerable gait speed for EMG amplitude analysis, and gender for pain intensity and performance in lumbar movement control (LMC) tests). Significant post-training improvement in pain intensity (p = 0.014) and overall performance of the LMC tests (p = 0.006) were found for those who received backward walking training. …”

Supplementary file of datasets. by Ellen Chan (22177558)

“…</p><p>Results</p><p>Two-way repeated measures analysis of covariance (ANCOVA) was adopted to minimize the confounding effect from covariates identified (maximal tolerable gait speed for EMG amplitude analysis, and gender for pain intensity and performance in lumbar movement control (LMC) tests). Significant post-training improvement in pain intensity (p = 0.014) and overall performance of the LMC tests (p = 0.006) were found for those who received backward walking training. …”

Table 1_Esmolol improves sepsis outcomes through cardiovascular and immune modulation.docx by Da Jing (404219)

“…Background<p>Sepsis poses significant mortality risks. Esmolol, a β1-adrenergic blocker, may improve outcomes through cardiovascular and immune modulation. …”

Supplementary Material for: Healing Diabetic Foot Ulcers with Topical Timolol Improves Healed Epithelial Integrity by figshare admin karger (2628495)

“…The use of a wheelchair was also associated with a significant decrease in transepidermal water loss (Estimate = -7.7, p=0.01). …”

Table 1_Molecular hybridization modification improves the stability and immunomodulatory activity of TP5 peptide.docx by Junyong Wang (3807964)

“…The half-life of YTP in plasma is significantly longer than that of YW12D and TP5. YTP also displays an improved ability to protect the host from CTX-induced weight loss and thymus and spleen indices decrease than YW12D and TP5. …”

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. …”

Contribution of individual models to the ensemble performance on the Lazzarotto <i>et al</i>. (2020) GUIDE-seq dataset. by Kai Kimata (22608153)

Modulation of performance during learning. by Daniel Ramandi (10047543)

Spectral-domain optical coherence tomography (SD-OCT) images taken from a 72-year-old female patient with neovascular age-related macular degeneration (nAMD) who received ranibizum... by Zheyao Gu (20910794)