Test Schedule. by Haotian Guo (6620120)

“…The cooling rate significantly affected the frost heave ratio: under closed conditions, the ratio decreased, whereas under open water supply conditions, the vertical frost heave displacement increased with higher cooling rates.Moisture migration within the specimen was notably different under the two replenishment conditions. …”

Temperature curve of sample T1. by Haotian Guo (6620120)

“…The cooling rate significantly affected the frost heave ratio: under closed conditions, the ratio decreased, whereas under open water supply conditions, the vertical frost heave displacement increased with higher cooling rates.Moisture migration within the specimen was notably different under the two replenishment conditions. …”

Table 1_Analysis of the microbiota of pregnant women in relation to weight gain during pregnancy – a pilot study.docx by Katarzyna Kosinska-Kaczynska (6794522)

“…While the difference was not statistically significant after correction for multiple testing, the Chao index showed a persistent trend toward reduced species richness in the study group. …”

Supplementary Material for: A case report of adult lead-poisoning followed by use of non-prescription Ayurvedic medication in Germany by figshare admin karger (2628495)

“…Abstract Introduction: This case report describes a 65-year-old female patient from Germany who developed clinically significant lead poisoning following the use of Ayurvedic herbal preparations provided by an unlicensed practitioner in a major German city. …”

Table_1_Higher oxidative balance score is associated with lower female infertility: a cross-sectional study.DOCX by Xiong Lei (3847897)

“…When OBS was used as a categorical variable, female infertility decreased by 60% in the highest OBS group compared with the lowest OBS group (OR, 0.40; 95% CI, 0.21 to 0.74). …”

Data Sheet 1_Dysregulation of melatonin rhythm in Parkinson’s and Huntington’s disease: a systematic review and meta-analysis.docx by Reema Priyanka Suram (22399759)

“…In manifest HD, both amplitude [RoM = 0.92, 95% CI (0.81 to 1.02); p = 0.00] and acrophase [RoM = 0.92, 95% CI (0.07 to 1.78); p = 0.03] significantly decreased. PD patients with sleep disorders had significantly higher melatonin concentrations than the non-sleep disorder group, with a significant test group difference of p = 0.00. …”

Data Sheet 4_Efficacy and safety of Shuxuening injection in intracerebral hemorrhage: a systematic review and meta-analysis.pdf by Wenting Song (822582)

“…Meanwhile, the incidence of AE in the treatment group was lower than that in the control group, with a statistically significant difference [RR = 0.63, 95%CI 0.41, 0.96].…”

Data Sheet 3_Efficacy and safety of Shuxuening injection in intracerebral hemorrhage: a systematic review and meta-analysis.pdf by Wenting Song (822582)

“…Meanwhile, the incidence of AE in the treatment group was lower than that in the control group, with a statistically significant difference [RR = 0.63, 95%CI 0.41, 0.96].…”

Data Sheet 2_Efficacy and safety of Shuxuening injection in intracerebral hemorrhage: a systematic review and meta-analysis.pdf by Wenting Song (822582)

“…Meanwhile, the incidence of AE in the treatment group was lower than that in the control group, with a statistically significant difference [RR = 0.63, 95%CI 0.41, 0.96].…”

Data Sheet 1_Efficacy and safety of Shuxuening injection in intracerebral hemorrhage: a systematic review and meta-analysis.pdf by Wenting Song (822582)

“…Meanwhile, the incidence of AE in the treatment group was lower than that in the control group, with a statistically significant difference [RR = 0.63, 95%CI 0.41, 0.96].…”

PCA-CGAN model parameter settings. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

MIT-BIH dataset proportion analysis chart. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

Wavelet transform preprocessing results. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

PCAECG_GAN. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

MIT dataset expansion quantities and Proportions. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

Experimental hardware and software environment. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

PCA-CGAN K-fold experiment table. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

Classification model parameter settings. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

MIT-BIH expanded dataset proportion chart. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”

AUROC Graphs of RF Model and ResNet. by Chao Tang (10925)

“…This research addresses core challenges in ECG signal classification—extremely imbalanced data, significant individual physiological differences, and difficulties in long sequence fitting—by proposing a Principal Component Analysis-based Conditional Generative Adversarial Network (PCA-CGAN). …”