Number of captured on-target sites and average site-based coverage for each capture efficiency experiment. by Amy Longtin (21409957)

Effect of voluntarily wheel running on DOX-induced renal dysfunction. by Xin Jiang (6348)

The numerical solution of model (1) for infected compartment vs. time with different scenarios of Phase 1 in the First Case: 1^<i>st</i> scenario, no lockdown is implemen... by Sara K. Al-Harbi (12418482)

“…<p>The numerical solution of model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0265779#pone.0265779.e002" target="_blank">(1)</a> for infected compartment vs. time with different scenarios of Phase 1 in the First Case: 1^<i>st</i> scenario, no lockdown is implemented; 2^<i>nd</i> scenario, no lockdown while <i>SD</i> increases; 3^<i>rd</i> scenario, lockdown increases; 4^<i>th</i> scenario, <i>SD</i> increases; 5^<i>th</i> scenario, lockdown decreases; 6^<i>th</i> scenario, <i>SD</i> decreases; 7^<i>th</i> scenario, lockdown and <i>SD</i> increases; 8^<i>th</i> scenario, lockdown decreases and <i>SD</i> increases.…”

The numerical solution of model (1) for infected compartment vs. time with different scenarios of Phase 4 in the First Case: 1^<i>st</i> scenario, no lockdown is implemen... by Sara K. Al-Harbi (12418482)

“…<p>The numerical solution of model <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0265779#pone.0265779.e002" target="_blank">(1)</a> for infected compartment vs. time with different scenarios of Phase 4 in the First Case: 1^<i>st</i> scenario, no lockdown is implemented; 2^<i>nd</i> scenario, no lockdown while <i>SD</i> increases; 3^<i>rd</i> scenario, lockdown increases; 4^<i>th</i> scenario, <i>SD</i> increases; 5^<i>th</i> scenario, lockdown decreases; 6^<i>th</i> scenario, <i>SD</i> decreases; 7^<i>th</i> scenario, lockdown and <i>SD</i> increases; 8^<i>th</i> scenario, lockdown decreases and <i>SD</i> increases.…”

Correlation in site-level methylation between TMS and EPIC array data after sample permutation. by Amy Longtin (21409957)

Associations between exposure to endocrine disrupting chemical (EDC) groups and growth trajectories for each fetal parameter, INMA, 2003-2008. by Jennifer Ish (12369119)

Number of captured on-target sites and average site-based coverage for each input amount. by Amy Longtin (21409957)

Number of captured on-target sites and average site-based coverage for each plexing strategy. by Amy Longtin (21409957)

Correlation in methylation across DNA fragmentation methods. by Amy Longtin (21409957)

Distribution of AdapTrans parameters learned during the neural fitting process as a function of frequency. by Ulysse Rançon (15451568)

Results from Ordinary Least Squares (OLS). by Muhummad Khairul Islam (21955544)

“…<div><p>This study aims to examine the impact of energy consumption, i.e., coal and gas, on environmental sustainability by utilizing CO2 emissions as a proxy to emphasize Environmental, Social, and Governance (ESG) practices in the electricity supply company of Malaysia. …”

Correlation Matrix. by Muhummad Khairul Islam (21955544)

“…<div><p>This study aims to examine the impact of energy consumption, i.e., coal and gas, on environmental sustainability by utilizing CO2 emissions as a proxy to emphasize Environmental, Social, and Governance (ESG) practices in the electricity supply company of Malaysia. …”

Multicollinearity Test. by Muhummad Khairul Islam (21955544)

“…<div><p>This study aims to examine the impact of energy consumption, i.e., coal and gas, on environmental sustainability by utilizing CO2 emissions as a proxy to emphasize Environmental, Social, and Governance (ESG) practices in the electricity supply company of Malaysia. …”

Descriptive Statistics. by Muhummad Khairul Islam (21955544)

“…<div><p>This study aims to examine the impact of energy consumption, i.e., coal and gas, on environmental sustainability by utilizing CO2 emissions as a proxy to emphasize Environmental, Social, and Governance (ESG) practices in the electricity supply company of Malaysia. …”

Fig 6 - by Giulio Contemori (7019876)

Understanding the Effect of Platinum Particle Size on Ethane Dehydrogenation and Hydrogenolysis: Particle-Based Microkinetic Modeling at Finite Conversion by Mubarak Bello (16715843)

“…The effect of platinum particle size on the kinetics and mechanism of ethane dehydrogenation (EDH) and hydrogenolysis (EH) is elucidated using first-principles and multiscale modeling. A particle-based microkinetic modeling (PB-MKM) approach is used to couple the MKMs for individual facets, i.e., Pt(111), Pt(100), and Pt(211), into a variable-size Pt nanoparticle catalyst model. …”

Understanding the Effect of Platinum Particle Size on Ethane Dehydrogenation and Hydrogenolysis: Particle-Based Microkinetic Modeling at Finite Conversion by Mubarak Bello (16715843)

“…The effect of platinum particle size on the kinetics and mechanism of ethane dehydrogenation (EDH) and hydrogenolysis (EH) is elucidated using first-principles and multiscale modeling. A particle-based microkinetic modeling (PB-MKM) approach is used to couple the MKMs for individual facets, i.e., Pt(111), Pt(100), and Pt(211), into a variable-size Pt nanoparticle catalyst model. …”

Understanding the Effect of Platinum Particle Size on Ethane Dehydrogenation and Hydrogenolysis: Particle-Based Microkinetic Modeling at Finite Conversion by Mubarak Bello (16715843)

“…The effect of platinum particle size on the kinetics and mechanism of ethane dehydrogenation (EDH) and hydrogenolysis (EH) is elucidated using first-principles and multiscale modeling. A particle-based microkinetic modeling (PB-MKM) approach is used to couple the MKMs for individual facets, i.e., Pt(111), Pt(100), and Pt(211), into a variable-size Pt nanoparticle catalyst model. …”

Understanding the Effect of Platinum Particle Size on Ethane Dehydrogenation and Hydrogenolysis: Particle-Based Microkinetic Modeling at Finite Conversion by Mubarak Bello (16715843)

“…The effect of platinum particle size on the kinetics and mechanism of ethane dehydrogenation (EDH) and hydrogenolysis (EH) is elucidated using first-principles and multiscale modeling. A particle-based microkinetic modeling (PB-MKM) approach is used to couple the MKMs for individual facets, i.e., Pt(111), Pt(100), and Pt(211), into a variable-size Pt nanoparticle catalyst model. …”

Trends in preferences. by Greg Carney (372057)