Data Sheet 1_The dynamics of lowland river sections of Danube and Tisza in the Carpathian basin.pdf by Imre M. Jánosi (7480598)

“…Almost all the water level and discharge records indicate a decadal decreasing trend for annual maximum values. …”

Supplementary file 1_Age-period-cohort analysis of syphilis epidemics in Eastern China, China, 2005–2024.docx by Zheyuan Ding (4281394)

“…The implementation of national syphilis control programs has achieved significant results. There is a need to strengthen the management of late-stage syphilis among older adults and enhance syphilis prevention and control efforts among adolescents.…”

Image 1_Age-period-cohort analysis of syphilis epidemics in Eastern China, China, 2005–2024.jpeg by Zheyuan Ding (4281394)

“…The implementation of national syphilis control programs has achieved significant results. There is a need to strengthen the management of late-stage syphilis among older adults and enhance syphilis prevention and control efforts among adolescents.…”

Image 3_Age-period-cohort analysis of syphilis epidemics in Eastern China, China, 2005–2024.jpeg by Zheyuan Ding (4281394)

“…The implementation of national syphilis control programs has achieved significant results. There is a need to strengthen the management of late-stage syphilis among older adults and enhance syphilis prevention and control efforts among adolescents.…”

Image 2_Age-period-cohort analysis of syphilis epidemics in Eastern China, China, 2005–2024.jpeg by Zheyuan Ding (4281394)

“…The implementation of national syphilis control programs has achieved significant results. There is a need to strengthen the management of late-stage syphilis among older adults and enhance syphilis prevention and control efforts among adolescents.…”

Swimming endurance training reduces T-wave amplitude and area in <i>Mib1</i>^<i>flox</i><i>;Tnnt2</i>^<i>Cre</i> mice. by Vítor S. Fernandes (21262991)

“…<p><b>(A)</b> Representative QRS complex and T-wave, with (A’) a close-up of the T-wave in WT and <i>Mib1</i>^<i>flox</i><i>;Tnnt2</i>^<i>Cre</i> mice before the swimming protocol. …”

60 Hz-induced neural entrainment. by MohammadAmin Alamalhoda (22386405)

“…The gray bar indicates the 50 Hz line noise, which was notch-filtered. A strong 60 Hz frequency component is evident from start to finish but decreases over the course of the study at day 5 and day 19. …”

Multivariate statistical analysis diagram. by Ying Zhang (40767)

“…<p><b>(a, b)</b> PLS-DA diagrams. The separation pattern was satisfactory, with significant differences in principal components among the groups, indicating that the metabolic profiles underwent significant alterations between different groups. …”

Table 1_Comparative transcriptomic and molecular biology analyses to explore potential immune responses to Vibrio parahaemolyticus challenge in Eriocheir sinensis.docx by Duanduan Chen (6860495)

“…<p>Vibrio parahaemolyticus is a significant pathogen affecting shrimp and crab farming, particularly strains carrying genes associated with acute hepatopancreatic necrosis syndrome. …”

Image 1_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 8_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 6_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 2_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 7_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 5_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 4_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Image 3_EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach.png by Eyad Talal Attar (22124251)

“…A Random Forest classifier reached 86. The system achieved a 7% accuracy rate in differentiating cognitive from meditative states while identifying P300 amplitude and frontal alpha power, together with beta power as significant predictors.…”

Supplementary file 1_Source apportionment and ecological risk of heavy metals in Taihu lake from 2020 to 2022.docx by Guangjing Bao (21837749)

“…Furthermore, the potential ecological risk exhibited a significant decreasing trend, with Z-values passing the 95% confidence interval significance test, except for S3. …”

Data Sheet 1_Global soil moisture dynamics: attribution of contributions and their association with GPP.docx by Yang Li (7082)

“…This study further integrates the MODIS MCD12C1 and GOSIF GPP datasets to explore the correlation between SM and GPP on a global scale. The results indicate that between 2000 and 2024, global Total Soil Moisture (TSM) shows a marked declining trend, with SM decreasing synchronously across all seasons. …”

Data Sheet 1_The longitudinal associations between filial piety belief and mobile phone addiction: from the perspective of self-determination theory.zip by Hua Wei (60877)

“…The results showed that reciprocal filial piety belief has a negative impact on mobile phone addiction, while authoritarian filial piety belief has no significant effect on mobile phone addiction. …”