Periodic Open Cellular Structures with Streamlined Elliptical Struts for the Intensification of Mass Transfer-Limited Catalytic Reactors by Claudio Ferroni (10972436)

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A sample choice question without a warning label. by Yulian Ding (5984591)

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Description of the warning label. by Yulian Ding (5984591)

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The effectiveness of a warning label on carbonated beverage consumption for consumers with different habit strengths. by Yulian Ding (5984591)

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The impact of a warning label on carbonated beverage consumption. by Yulian Ding (5984591)

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Flow chart of the study. by Yulian Ding (5984591)

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A sample choice question with a warning label. by Yulian Ding (5984591)

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Consumption frequencies of different types of SSBs. by Yulian Ding (5984591)

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Summary statistics of the sample. by Yulian Ding (5984591)

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The impact of health knowledge and obesity status on the effectiveness of a warning label. by Yulian Ding (5984591)

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Product attributes and attribute levels. by Yulian Ding (5984591)

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Dataset used in this study. by Yulian Ding (5984591)

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Socio-demographics of the subsamples with different habit strengths. by Yulian Ding (5984591)

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Definitions of the variables. by Yulian Ding (5984591)

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Key significant pathways in the final models of self-compassion. by Eriko Takahashi (22608061)

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Significant inter-relationships between baseline variables and MSCC or MCS. by Harshit Arora (22008280)

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Average of % peptides counts for different classes of proteins at different germination time points and significant p-value indicated as compared to soaked sample (*p< 0.05, **p<0.01, ***p<0.001) for garbanzo trypsinised with shades of green showing increase and red showing decrease with respect to soaked. by Indrani Bera (804948)

“…<p>Average of % peptides counts for different classes of proteins at different germination time points and significant p-value indicated as compared to soaked sample (*p< 0.05, **p<0.01, ***p<0.001) for garbanzo trypsinised with shades of green showing increase and red showing decrease with respect to soaked.…”

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error manual calculation process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error measurement results statistics. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”