External and internal view of the Omni mixer [ by Tek Raj Gyawali (20550560)

“…Panels reinforced with thinner PVA fibers exhibited superior performance in resisting compressive and impact loads. This enabled a reduction in fiber content to 1.2% (a 60% decrease) and panel thickness to 22 mm (a 4.35% decrease) compared to panels with thicker fibers. …”

Required properties of sand. by Tek Raj Gyawali (20550560)

“…Panels reinforced with thinner PVA fibers exhibited superior performance in resisting compressive and impact loads. This enabled a reduction in fiber content to 1.2% (a 60% decrease) and panel thickness to 22 mm (a 4.35% decrease) compared to panels with thicker fibers. …”

Classification of panels after the impact test. by Tek Raj Gyawali (20550560)

“…Panels reinforced with thinner PVA fibers exhibited superior performance in resisting compressive and impact loads. This enabled a reduction in fiber content to 1.2% (a 60% decrease) and panel thickness to 22 mm (a 4.35% decrease) compared to panels with thicker fibers. …”

Static loading procedure. by Tek Raj Gyawali (20550560)

“…Panels reinforced with thinner PVA fibers exhibited superior performance in resisting compressive and impact loads. This enabled a reduction in fiber content to 1.2% (a 60% decrease) and panel thickness to 22 mm (a 4.35% decrease) compared to panels with thicker fibers. …”

Cytokines produced by CD4+ T cells after <i>in vitro</i> restimulation with rTcj2 protein. by Leroy Versteeg (4248760)

Table 1_A national framework for transition to precision medicine.docx by Samaneh Karimi Esboei (20623664)

“…The statistical sample of the study comprised PM specialists, researchers, and patients whose PM plays a significant role in their diagnosis and treatment. …”

ZIKV infection enriches the HLA Class I pathway in brain tumour cells. by Matt Sherwood (22530221)

“…Normalised enrichment score (NES) denotes the degree to which the enrichment increased (+) or decreased (-). GSEA analysis significance is defined by p ≤ 0.05 and FDR ≤ 0.25. …”

Assessing Quality of Referrals to a Community-Based Chronic Pain Clinic by Angela Mailis (19960223)

“…Half of the non-resubmitted referrals could have been accepted if the referring provider had sent in the missing information.</p> <p>A significant number of referrals to our pain clinic (primarily from PCPs) are rejected for mainly avoidable reasons. …”

Thermodynamic parameters. by Jianqing Jia (21001506)

“…<div><p>Frost heave is a most common form of tunnel defect in cold regions. …”

Valve luminal distance and opening time upon valve malformation. by Christian Meyer (6035)

Primers used for real-time qPCR. by Eloise Parry-Nweye (7548998)

“…The results show that the infectivity of aerosolized Phi6 in air decreased by ≥ 1 log₁₀ as the relative humidity (RH) increased from 25% to 75% but then increased by ≥ 1 log₁₀ as the RH further increased to 85%, resulting in a characteristic V-shape curve which varied with exposure time. …”

IDA flowchart. by Jun Zhao (59250)

“…This offers a scientific foundation for designing and constructing prefabricated shear walls.…”

Numerical simulation model. by Jianqing Jia (21001506)

“…<div><p>Frost heave is a most common form of tunnel defect in cold regions. …”

Reliability and failure probability. by Jianqing Jia (21001506)

“…<div><p>Frost heave is a most common form of tunnel defect in cold regions. …”

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. …”