Principal coordinates analysis (PCoA). by Wararak Choovanichvong (22110371)

“…Analysis of bacterial abundance revealed a shift in trends as the disease combined from control to NSESKD and SESKD group, respectively, across 7 genera: <i><i>Actinobacillus</i></i>, <i>TM7x</i>, <i><i>Capnocytophaga</i></i>, <i><i>Neisseria</i></i>, and <i><i>Leptotrichia</i></i> increased in abundance, while <i><i>Actinomyces</i></i> and <i><i>Atopobium</i></i> decreased. Linear discriminant analysis effect size (LEfSe) identified <i><i>Leptotrichia</i></i> as a potential biomarker for ESKD (both with and without sarcopenia).…”

Experimental and Numerical Investigations of Soot Formation in the Laminar to Turbulent Transition of an Acetylene Diffusion Flame by Shijun Chen (835302)

“…Results from different regimes indicate the following: (1) In the laminar state, <i>ṁ</i>_soot increased linearly with <i>Re</i>, with a growth rate positively correlated with the tube diameter. (2) After entering the transitional state, <i>ṁ</i>_soot decreased exponentially by over 95%; <i>T</i> gradually increased by 150 K; and both SPL and the standard deviation of <i>T</i> (σ_<i>T</i>) initially rose and then declined. (3) After entering the fully turbulent state, SPL increased again whereas σ_<i>T</i> stabilized at 14. …”

Clustering analysis of total and active RNAP II at genes during the transition from G1 to G2. by Douglas Maya-Miles (7024967)

Sequential viral infection modulates the intestinal bacterial microbiome. by Yuhao Li (1559569)

Mexican warning label system. by Claudia Calderon (266352)

“…Similarly, the FOPWL decreased the perceived healthiness of both nectar with “excess sugars” and nectar with NNS. …”

S1 Dataset - by Claudia Calderon (266352)

“…Similarly, the FOPWL decreased the perceived healthiness of both nectar with “excess sugars” and nectar with NNS. …”

Images with FOPWL by time of data collection. by Claudia Calderon (266352)

“…Similarly, the FOPWL decreased the perceived healthiness of both nectar with “excess sugars” and nectar with NNS. …”

IFN-responsive and anti-viral pathways are induced in γδ T cells post-HIV-1 acquisition. by Gina L. Griffith (20649097)

Benchmark regression results. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Heterogeneity test. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

S1 File - by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

The robustness test. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Mechanistic testing. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Descriptive statistics of variables. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Endogenous treatment. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Analysis of industry linkage effects. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Analysis of peer effects. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Mean daily sediment transport (g m^-2 day^-1) under different vegetation types and soil cover in southeastern Utah, USA, 2004 to 2018. by Andrew Kulmatiski (833256)

Highly Sensitive and Selective Electrochemical Sensor via Cu-BTC/Au@Cu-BTC Modified Screen-Printed Electrode for the Detection of Chemical Agents by Xiaosen Li (6263651)

“…Chemical agents present significant threat to international peace, security, and human health due to their potential toxicity. …”

Principal component analysis of soil parameters. by Wasihun Mengiste (22470304)

“…The data were analyzed using the General Linear Model (GLM) procedure in SAS version 9.4. The result showed that slope gradients, soil depths, and slope gradients interacting with soil depths had very highly, highly and significant effects on selected soil parameters, exchangeable bases, and extractable micronutrients. …”