System configuration of HEARTS. by Atsushi Nakazawa (15892700)

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Face detection rate. by Atsushi Nakazawa (15892700)

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Occurrence rate of eye contact. by Atsushi Nakazawa (15892700)

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Participants. by Atsushi Nakazawa (15892700)

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Utterance. by Atsushi Nakazawa (15892700)

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Gaze, speech scores displayed on HEARTS. by Atsushi Nakazawa (15892700)

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Face-to-face distance ([mm]). by Atsushi Nakazawa (15892700)

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Facial expressions of avatar. by Atsushi Nakazawa (15892700)

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Overview of experiment. by Atsushi Nakazawa (15892700)

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Face-to-face angle (yaw rotation [deg]). by Atsushi Nakazawa (15892700)

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Image 3_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif by Stefanie Wagner (743707)

“…These results were not detectable by standard 16S analysis based on relative abundances. Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”

Image 1_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif by Stefanie Wagner (743707)

“…These results were not detectable by standard 16S analysis based on relative abundances. Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”

Image 2_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif by Stefanie Wagner (743707)

“…These results were not detectable by standard 16S analysis based on relative abundances. Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”

Image 4_Absolute abundance calculation enhances the significance of microbiome data in antibiotic treatment studies.tif by Stefanie Wagner (743707)

“…These results were not detectable by standard 16S analysis based on relative abundances. Here, GCN correction additionally uncovered significant decreases of Lactobacillus and Faecalibacterium. …”

Significance analysis results. by Yicheng Long (366418)

“…<div><p>Amid substantial capital influx and the rapid evolution of online user groups, the increasing complexity of user behavior poses significant challenges to cybersecurity, particularly in the domain of vulnerability prediction. …”

P values of Kruskal–Wallis test at 95% significance level. by Fahd Saeed Alakbari (10701871)

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Time and flowrate used for proteomics. by Kevin J. Kokesh (19859571)

“…Taken together, MARCKS protein is upregulated in CF cells and there is decreased phosphorylation of the protein due to a decrease in PKC activity and presumably increased cathepsin B mediated proteolysis of the protein after <i>M</i>. …”

Terrain variables used in the present study, along with their geomorphological significance. Sources: [92,94–102]. by Manuel La Licata (20476906)

The hierarchy of the data and the VAE used in this study. by Richard Felius (19803632)

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Bacterial strains used in this study. by Malin-Theres Seffer (14808772)

“…Within the first four hours, the number of bacteria decreased continuously and the reduction in bacteria reached statistical significance after two hours of treatment (percentage reduction 64%, p-value 0.01165). …”