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. …”

Table 1_Association between composite dietary antioxidant index and increased urinary albumin excretion: a population-based study.docx by Shaopeng Li (820947)

“…Those in higher CDAI quartiles showed a reduced likelihood of elevated ACR. The prevalence of increased ACR decreased across the CDAI quartiles from 13.89% in Q1 to 10.11% in Q4. …”

Plots summarising the fixed effect coefficient estimates from fitting the generalised linear mixed effects models to contact matrices calculated at a resolution of 10 kb. by Tze Yee Lim (22057822)

Image 4_Pediatric kidney transplant recipients are at an increased risk for dysbiosis.jpeg by Gizem Yılmaz (20641691)

“…In addition, KTx recipients with a history of frequent urinary tract infections, diarrhea and reduced GFR showed significant increases in bacterial abundance (p < 0.05 for all).…”

Image 1_Pediatric kidney transplant recipients are at an increased risk for dysbiosis.jpeg by Gizem Yılmaz (20641691)

“…In addition, KTx recipients with a history of frequent urinary tract infections, diarrhea and reduced GFR showed significant increases in bacterial abundance (p < 0.05 for all).…”

Image 3_Pediatric kidney transplant recipients are at an increased risk for dysbiosis.jpeg by Gizem Yılmaz (20641691)

“…In addition, KTx recipients with a history of frequent urinary tract infections, diarrhea and reduced GFR showed significant increases in bacterial abundance (p < 0.05 for all).…”

Image 2_Pediatric kidney transplant recipients are at an increased risk for dysbiosis.jpeg by Gizem Yılmaz (20641691)

“…In addition, KTx recipients with a history of frequent urinary tract infections, diarrhea and reduced GFR showed significant increases in bacterial abundance (p < 0.05 for all).…”

<b>Data from: </b><b>Experimentally increased food availability allows for earlier departure in a long-distance migratory shorebird</b> by Thomas Lameris (20888213)

“…These were typically birds did not initiate body mass increase and kept a low body mass throughout the experiment. …”

Data Sheet 1_Non-linear association between the dietary index for gut microbiota and the atherogenic index of plasma: insights from a cross-sectional study.docx by Tian-Ding Liu (21659201)

“…Restricted cubic spline (RCS) analysis identified a significant non-linear dose-response relationship (P for non-linearity = 0.018) with a threshold at DI-GM = 3.467. …”

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. …”