Simulation of asphalt density. by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Basic properties of asphalt at different aging times. by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Basic performance results of aged asphalt regenerated from WEO. by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Performance index of 70# MA. by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Original data. by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Microscopic morphology of different asphalts (200 × , 1000 × , and 1500×). by Yi Wang (32470)

Subjects: “…diffusion coefficients increased…”

Minimal data set. by Xiaoxia Liu (294088)

“…In contrast, with a negative Soret coefficient, the growth rate of the spherical crystals increases as the coefficient decreases, and the solute concentration near the interface decreases. …”

Predictors in ordinal regression model for GDS. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Classification of hand grip strength. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Rating scale for functional severity [28]. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Regression model coefficients. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

ICOPE screening positive participant’s responses. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

WHO BMI classification for adults. by Shane Naidoo (20148021)

“…In an ordinal regression model BMI was a significant predictor (<i>B</i> = .10, <i>p</i> = .007) for increases in depression. …”

Receiver operating characteristic curve analyses for the prediction of hepatitis C. by Lu Han (151620)

Subjects:

Exploring the correlation between systemic inflammation biomarkers and HCV infection (logarithm base 2). by Lu Han (151620)

Subjects:

Exclusion and enrollment summary from NHANES. by Lu Han (151620)

Subjects:

Demographic information and baseline population characteristics. by Lu Han (151620)

Subjects:

Stratified associations between systemic inflammation biomarkers and hepatitis C (OR 95%, <i>P</i> value, LOG base 2). by Lu Han (151620)

Subjects:

General addictive models demonstrate the relationship between systemic inflammatory biomarkers and anti-HCV. by Lu Han (151620)

Subjects:

Comparison of systemic inflammation biomarkers in infected and uninfected populations. by Lu Han (151620)

Subjects: