No association between the vitamin D pathway gene polymorphisms and bone biomarkers response to calcium and low dose calcitriol supplementation in postmenopausal Chinese women: a o... by Jiemei Gu (5477177)

Table 3_Association between platelet-to-red cell distribution width ratio and all-cause mortality in critically ill patients with non-traumatic cerebral hemorrhage: a retrospective... by Rongrong Lu (322302)

“…As PRR increased, restrictive cubic splines showed a progressive decrease in the probability of all-cause mortality. …”

Table 1_Association between platelet-to-red cell distribution width ratio and all-cause mortality in critically ill patients with non-traumatic cerebral hemorrhage: a retrospective... by Rongrong Lu (322302)

“…As PRR increased, restrictive cubic splines showed a progressive decrease in the probability of all-cause mortality. …”

Table 2_Association between platelet-to-red cell distribution width ratio and all-cause mortality in critically ill patients with non-traumatic cerebral hemorrhage: a retrospective... by Rongrong Lu (322302)

“…As PRR increased, restrictive cubic splines showed a progressive decrease in the probability of all-cause mortality. …”

Data_Sheet_1_A pooled analysis of temporal trends in the prevalence of anxiety-induced sleep loss among adolescents aged 12–15 years across 29 countries.docx by Guodong Xu (479781)

“…</p>Conclusion<p>Trends in the prevalence of anxiety-induced sleep loss in adolescents varied significantly across different countries. Generally, a stable trend was observed in 21 of the 29 countries surveyed. …”

Raw data for MaMsb2.xlsxSupplemental materials for MaMsb2, a signaling mucin, is involved in conidiation, stress tolerances, and virulence in the entomopathogenic fungus Metarhiziu... by Kai Jin (20368413)

Changes in the concentration of lactate, bicarbonate (HCO), base excess (BE) and chloride (Cl) after a patient with septic shock was placed on high-volume hemofiltration (HVHF) and... by Rinaldo Bellomo (982)

Deficits and Disparities in Early Uptake of GLP-1 Receptor Agonists and SGLT2 Inhibitors among Medicare-insured Adults Following a New Diagnosis of Cardiovascular Disease or Heart... by Sara J. Cromer (13136821)

Effects of Low-Fat, Mediterranean, or Low-Carbohydrate Weight Loss Diets on Serum Urate and Cardiometabolic Risk Factors - A Secondary Analysis of the Dietary Intervention Randomiz... by Chio Yokose (9221485)

A Kinetic Model of CO₂ Absorption in Molten CaO-CaF₂-CaCl₂ (Supporting Information) by Sondre G. IVELAND (17999140)

Effects of Concurrent Training and a Multi-Ingredient Performance Supplement Containing <i>Rhodiola rosea</i> and <i>Cordyceps sinensis</i> on Body Composition, Performance, and He... by Vince C. Kreipke, PhD (9540472)

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. …”

Table_1_Probiotics, Prebiotics, and Synbiotics Improve Uremic, Inflammatory, and Gastrointestinal Symptoms in End-Stage Renal Disease With Dialysis: A Network Meta-Analysis of Rand... by Zixian Yu (8876978)

Table 1_Global and regional burdens of opioid use disorder from 1990 to 2021, with future forecasts to 2050: a systematic analysis for the global burden of disease study 2021.docx by Juanzhao Cao (22651742)

Table_2_Probiotics, Prebiotics, and Synbiotics Improve Uremic, Inflammatory, and Gastrointestinal Symptoms in End-Stage Renal Disease With Dialysis: A Network Meta-Analysis of Rand... by Zixian Yu (8876978)

Table_1_Probiotics, Prebiotics, and Synbiotics Improve Uremic, Inflammatory, and Gastrointestinal Symptoms in End-Stage Renal Disease With Dialysis: A Network Meta-Analysis of Rand... by Zixian Yu (8876978)