PCAECG-GAN K-fold experiment table. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Pseudocode Table. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Ablation Experiment Results. by Chao Tang (10925)

“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

Wetland classification scheme for the contemporary period. by Nic Gedney (19762301)

Decadal seasonality of the hydrological cycle over the wetland regions. by Nic Gedney (19762301)

Trend components extracted from the X11 process for various types of viral hepatitis in Zhejiang Province from 2004 to 2023. by Ming Xue (591840)

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Example of coloration measurement taken in ImageJ for <i>M</i>. <i>mercenaria</i> specimen w48 at the conclusion of the 20.5-week experiment. by Teagan McMahon (20108036)

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Forest plot of the scaling exponent of hepatitis incidence from 2004 to 2023 (a. forest plot of hepatitis A; b. forest plot of hepatitis B; c. forest plot of hepatitis C; d. forest... by Ming Xue (591840)

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Descriptive statistics of variables. by Yanling Li (269030)

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The proportional change in maximum height for the five study groups. by Teagan McMahon (20108036)

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Seasonal components extracted from the X11 process of various types of viral hepatitis in Zhejiang Province from 2004 to 2023. by Ming Xue (591840)

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Parameter estimates of linear mixed effects models for juvenile <i>M</i>. <i>mercenaria</i>, juvenile <i>M</i>. <i>arenaria</i> and juvenile <i>A</i>. <i>islandica</i> proportional... by Teagan McMahon (20108036)

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Subset of juvenile <i>M</i>. <i>arenaria</i> specimens at the end of the experiment. by Teagan McMahon (20108036)

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Matched kernel density function diagram. by Yanling Li (269030)

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Growth and color data for all specimens and tank temperature and pH conditions. by Teagan McMahon (20108036)

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Schematic of the experimental design of the pH and temperature-controlled culture experiment in Schiller Coastal Studies Center (SCSC; Bowdoin College, Orr’s Island, ME). by Teagan McMahon (20108036)

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Average experimental conditions (± standard deviation) for each tank. by Teagan McMahon (20108036)

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Matching estimation results of propensity score. by Yanling Li (269030)

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Sample balance test. by Yanling Li (269030)

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Visual examples of the change in maximum height measure. by Teagan McMahon (20108036)

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