Data Sheet 1_Demand-resource evaluations and post-performance thoughts in classical music students: how they are linked and influenced by music performance anxiety, audience, and t... by Ludovic Rey (21335090)

“…These states can be quantified using the Demand Resource Evaluation Score (DRES), calculated as the difference between resource and demand evaluations, with higher values indicating a greater challenge-type response. …”

Image 1_The effect of Traumeel LT ad us. vet. on the perioperative inflammatory response after castration of stallions: a prospective, randomized, double-blinded study.tif by Julia Laves (19779357)

“…All stallions had the highest pain summary score 8 hours after surgery, with decreasing values thereafter. The pain scores were not statistically different at any time point. …”

Table 1_The effect of Traumeel LT ad us. vet. on the perioperative inflammatory response after castration of stallions: a prospective, randomized, double-blinded study.docx by Julia Laves (19779357)

“…All stallions had the highest pain summary score 8 hours after surgery, with decreasing values thereafter. The pain scores were not statistically different at any time point. …”

Data Sheet 1_Exploratory study on the ascending pain pathway in patients with chronic neck and shoulder pain based on combined brain and spinal cord diffusion tensor imaging.docx by Zhiqiang Qiu (4603993)

“…FA values of the left STT (C2 segment, C5 segment) and right STT (C1 segment, C2 segment) were significantly decreased in bilateral cervical STTs of CNSP patients; MD values of the left STT (C1 segment, C2 segment, C5 segment) and right STT (C1 segment, C5 segment) were significantly increased (p < 0.05). …”

Table 1_Assessment of various salt water stresses with mineralization on plant growth and antioxidants activity to regulate oxidative stress and ROS scavenging of halophyte ice pla... by Xinchao Ma (22249096)

“…The specific configuration method of the composite saline-alkali solution is to mix Na₂SO₄, NaCl, NaHCO₃, CaCl₂, MgCl₂ in the proportion of 8:8:1:1:1 on the basis of distilled water. The results indicated that the T6 treatment (saline-alkali solution of 30 g/L) strongly decreased the plant height, stem thickness, leaf area and SPAD value of ice plants, and obviously suppressed the shoot and root biomass with the increase in salinity. …”

Related to Fig 3. by Mohammad Nafees Ansari (22232505)

“…(<b>K–N</b>) Absolute quantification (mean ± SEM, <i>n</i> = 3–4) of GM3 (K), GD3 (L), GM2 (M), and GM1 (N) gangliosides shows an increase of GD3 and GM2 gangliosides and a decrease of GM3 and GM1 gangliosides in BT-474_ZFX^OE cells. …”

Table 1_Burden of hypertensive heart disease attributed to metabolic factors from 1990 to 2021 at global, regional, and national levels: an analysis of the global burden of disease... by Bo Peng (273834)

Table 1_COVID-19 pandemic increased ESKAPEEc bloodstream infections and amplified carbapenem resistance in Chinese children: a multicenter surveillance study (2016–2023).xls by Xiaoqiang Li (612879)

Data Sheet 1_Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned.pdf by Marketa Ciharova (8991782)

“…College students (n = 42; M age = 20.79, 69% female) completed a self-reported stress visual analogue scale at five time-points: After the initial resting period (P1), during the three stress-inducing tasks (i.e., preparation for a presentation, a presentation task, and an arithmetic task, P2-4) and after a recovery period (P5). …”

RICTOR regulates UGCG expression via transcription factor Zinc Finger X-linked (ZFX). by Mohammad Nafees Ansari (22232505)

“…<b>(B)</b> Results from qRT-PCR (mean ± SEM, <i>n</i> = 3) confirm reduced expression of RICTOR-regulated <i>ELF1</i>, <i>ZFX</i>, and <i>CTCF</i> transcription factors in MCF-7_RICTOR^SH cells. …”

Table 1_Global, regional, and national burden of self-harm among adolescents aged 10-24 years from 1990 to 2021, temporal trends, health inequities and projection to 2041.xlsx by Jiang Tan (260415)

Figure 6 from Gut Microbiome Profiling in Eμ-TCL1 Mice Reveals Intestinal Changes and a Dysbiotic Signature Specific to Chronic Lymphocytic Leukemia by Sydney A. Skupa (18597728)

“…<b>B,</b> CLL disease burden was measured by the percentage of CD45⁺/CD19⁺/CD5⁺ cells in the peripheral blood via flow cytometric analysis beginning at 1 week after engraftment (<i>n</i> = 10 mice/cohort). …”

Presentation 1_Pediatric healthcare service utilization after the end of COVID-19 state of emergency in Northern Italy: a 6-year quasi-experimental study using interrupted time-ser... by Matteo Puntoni (4901191)

“…Mental health-related hospitalizations exhibited the largest increase, peaking in the first months of the post-pandemic year (level change, Hospitalization Rate Ratio (HRR)2.57, 95%CI 1.61–4.12), then decreasing slightly in the last months but still maintaining much higher than pre-pandemic values. …”

Table 1_Pediatric healthcare service utilization after the end of COVID-19 state of emergency in Northern Italy: a 6-year quasi-experimental study using interrupted time-series ana... by Matteo Puntoni (4901191)

“…Mental health-related hospitalizations exhibited the largest increase, peaking in the first months of the post-pandemic year (level change, Hospitalization Rate Ratio (HRR)2.57, 95%CI 1.61–4.12), then decreasing slightly in the last months but still maintaining much higher than pre-pandemic values. …”

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. …”

Scree plot curve for five sets of models for the upper auricle. by Hitoshi Biwasaka (19923867)