Mean (95% CI) and standard deviation of VAS Score (mm) before & after intervention between two group during 1-houre standing. Intervention: using footrest with/without changing arm... by Saeedeh Abbasi (9423189)

Mean muscle activation patterns across the gait cycle during walking with Body Weight Support (BWS) for <i>A)</i> able-bodied individuals and <i>B)</i> individuals after stroke dur... by Sanne Ettema (18786312)

Post-mortem lesions of chickens with decreased egg production in Yancheng in 2023. by Yan Wang (15435)

PVS_ratio changes, ΔPVS_ratio, for different radiation doses within each treatment period: 0M–3M(a), 3M–12M(b), and 12M–FollowUp(c). by Ruitian Song (11045127)

Participants enrollment. by Chikondi Maluwa (20660522)

“…Among the 422 caregivers who participated in the study, 267 (63.2%) were females and mean age was 44.94 years. The baseline mean knowledge level score was 9.5 (38.0%) and rose to 21.08 (84.3%) p = 0.000 immediate post-health education and a 2.1% decrease 20.54 (82.2%) p<0.001 at week six from the immediate post health education score. …”

KAP assessment scores (n = 422). by Chikondi Maluwa (20660522)

“…Among the 422 caregivers who participated in the study, 267 (63.2%) were females and mean age was 44.94 years. The baseline mean knowledge level score was 9.5 (38.0%) and rose to 21.08 (84.3%) p = 0.000 immediate post-health education and a 2.1% decrease 20.54 (82.2%) p<0.001 at week six from the immediate post health education score. …”

PVS_volume changes, ΔPVS_volumes, for various radiation doses within each treatment period: 0M–3M(a), 3M–12M(b), and 12M–FollowUp(c). by Ruitian Song (11045127)

Trust levels before and after the COVID-19 pandemic (n = 10,000). by Alain Abi-Rizk (8549358)

The influence of H₂O₂ on <i>P</i>. <i>berghei</i> infection in <i>A</i>. <i>stephensi</i>. by Li Gao (131516)

Contact angle between solid and liquid. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

Diagram of the experimental equipment. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

Sedimentation experimental device. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

The wetting feature of compound solutions. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

Absorption peaks of groups. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

Infrared spectrogram of lignite. by Xinhui Luo (11880086)

“…We measured the performance of these solutions and revealed that the AES + AEO-9 blend demonstrated a significant synergistic effect, markedly enhancing the capture efficiency of water for lignite dust.…”

Each group’s performance on behavioral tests. by Wenbin Wu (292223)

Improvement effect of lactoferrin and Coenzyme Q10 on body composition of mice with sarcopenia. by Wenbin Wu (292223)

Overall and domain-specific mean readiness score by survey years, 2014 and 2017. by Rajon Banik (12066099)

Baseline characteristics of participants. by Hyungjong Park (10147327)

“…In the multivariable Cox regression analysis, eGFR > 120 mL/min ∙ 1.73 m² was associated with a decreased risk of dyslipidemia (HR: 0.35; 95% CI [0.34–0.36]). …”

Detailed information of the observation datasets. by Weidong Ji (129916)

“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”