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 non-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 non-trypsinised with shades of green showing increase and red showing decrease with respect to soaked.…”

Log2 fold change (FC) of the overlaps of lipid metabolites between the study groups and those significant metabolites that appear exclusively in a single group (unique) represented... by Laia Bertran (3685147)

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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Results of the mediation model test for the elevated inhibition function in the relationship between elevated mindfulness level and decreased mobile phone addiction index. by Jizhao Li (5856650)

Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013. by Qian Cai (112039)

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The yearly numerator, denominator and rate of incident opioid users, L-TOT users and L-TOT discontinuers from 2009 to 2019. by Qian Cai (112039)

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Incidence rate ratios of negative binominal regression models for yearly rates of incident opioid users, L-TOT users and L-TOT discontinuers during 2009–2013 and 2015–2019. by Qian Cai (112039)

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Demographic, comorbidity, concurrent drug, and opioid characteristics, among L-TOT users and L-TOT discontinuers between 2009–2019. by Qian Cai (112039)

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