Soil sample preparation process. 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. …”

Freezing of soil samples. 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. …”

Local schematic diagram of freezing device. 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 D1. 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. …”

The apparent cold structure of soil. 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. …”

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. …”

Supplementary Material for: Adverse Prognosis in Membranous Nephropathy with PLA2R1 Epitope Spreading: A Prospective Study by figshare admin karger (2628495)

“…A higher baseline level of anti-CTLD1 was notably linked to a lower likelihood of remission. …”

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). …”