Axial length and width. by Harry A. Quigley (695817)

HPx1 expression is controlled by dietary heme and the E75 transcription factor. by Octavio A. C. Talyuli (4285141)

Average IOP after bead injection glaucoma. by Harry A. Quigley (695817)

Unfixed Peripapillary Thickness. by Harry A. Quigley (695817)

Fig 6 - by Torsten Schober (20485754)

Fig 5 - by Torsten Schober (20485754)

Fig 4 - by Torsten Schober (20485754)

RTPCR of angiotensin receptor expression. by Harry A. Quigley (695817)

Top 10 important features according to the average decrease in Gini index over the 18 training models (features with a higher decrease tend to better split mixed nodes into single... by Remy Klaassen (3903154)

Mean mitochondrial DNA content in response to benzo<i>(a)</i>pyrene. by Nicky Pieters (409800)

“…<p>Mean mitochondrial DNA (mtDNA) content of human TK6 cells exposed to 0; 0.05; 0.5; 5; 50 and 500 µM benzo<i>(a)</i>pyrene (BAP). …”

Paeameter ranges and optimal values. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Improved random forest algorithm. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Datasets used in the study area. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Evaluation of the improved random forest model. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Comparison of model metrics. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Flowchart of population spatialization. by Zhen Zhao (159931)

“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”

Patterns of lifetime use of substances by gender. by Daniel Waiganjo Kinyanjui (15877725)

“…The lifetime prevalence of substance use was 41.5%, while that of alcohol use was 36%. For both, a higher mean neuroticism score [substance use- (AOR 1.05, 95%CI; 1, 1.10: p = 0.013); alcohol use- (AOR 1.04, 95%CI; 0.99, 1.09: p = 0.032)] showed increased odds of lifetime use, while a higher mean agreeableness score [substance use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.008); alcohol use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.032)] showed decreased odds of lifetime use. …”

S1 Data - by Daniel Waiganjo Kinyanjui (15877725)

“…The lifetime prevalence of substance use was 41.5%, while that of alcohol use was 36%. For both, a higher mean neuroticism score [substance use- (AOR 1.05, 95%CI; 1, 1.10: p = 0.013); alcohol use- (AOR 1.04, 95%CI; 0.99, 1.09: p = 0.032)] showed increased odds of lifetime use, while a higher mean agreeableness score [substance use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.008); alcohol use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.032)] showed decreased odds of lifetime use. …”

Factors associated with substance use. by Daniel Waiganjo Kinyanjui (15877725)

“…The lifetime prevalence of substance use was 41.5%, while that of alcohol use was 36%. For both, a higher mean neuroticism score [substance use- (AOR 1.05, 95%CI; 1, 1.10: p = 0.013); alcohol use- (AOR 1.04, 95%CI; 0.99, 1.09: p = 0.032)] showed increased odds of lifetime use, while a higher mean agreeableness score [substance use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.008); alcohol use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.032)] showed decreased odds of lifetime use. …”

Factors associated with personality traits. by Daniel Waiganjo Kinyanjui (15877725)

“…The lifetime prevalence of substance use was 41.5%, while that of alcohol use was 36%. For both, a higher mean neuroticism score [substance use- (AOR 1.05, 95%CI; 1, 1.10: p = 0.013); alcohol use- (AOR 1.04, 95%CI; 0.99, 1.09: p = 0.032)] showed increased odds of lifetime use, while a higher mean agreeableness score [substance use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.008); alcohol use- (AOR 0.99, 95%CI; 0.95, 1.02: p = 0.032)] showed decreased odds of lifetime use. …”