Showing 1,681 - 1,700 results of 7,348 for search 'significantly ((((((we decrease) OR (nn decrease))) OR (linear decrease))) OR (larger decrease))', query time: 0.45s Refine Results
  1. 1681

    S1 File - by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  2. 1682

    The robustness test. by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  3. 1683

    Mechanistic testing. by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  4. 1684

    Descriptive statistics of variables. by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  5. 1685

    Endogenous treatment. by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  6. 1686

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

    Published 2024
    “…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. …”
  7. 1687

    Analysis of peer effects. by Pengyu Yang (2668450)

    Published 2024
    “…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. …”
  8. 1688

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

    Published 2025
    “…Consistently, we show that although material properties may impact viral persistence, changes in the local humidity more significantly influence viral persistence on fomites. …”
  9. 1689
  10. 1690
  11. 1691
  12. 1692

    Model selection based on best fit. by Angelina Mageni Lutambi (22097223)

    Published 2025
    “…<div><p>Malaria remains a significant public health challenge, particularly among vulnerable populations in high-burden countries like Tanzania. …”
  13. 1693

    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)

    Published 2025
    “…Chemical agents present significant threat to international peace, security, and human health due to their potential toxicity. …”
  14. 1694
  15. 1695

    Basic characteristics included in the study. by Juan Gu (288925)

    Published 2025
    “…</p><p>Methods and analysis</p><p>We searched PubMed, Cochrane Library, Embase, and Web of Science for cohort studies published up to June 21, 2024, using relevant medical subject headings (MeSH) and keywords. …”
  16. 1696

    Publication bias of the risk of all groups. by Juan Gu (288925)

    Published 2025
    “…</p><p>Methods and analysis</p><p>We searched PubMed, Cochrane Library, Embase, and Web of Science for cohort studies published up to June 21, 2024, using relevant medical subject headings (MeSH) and keywords. …”
  17. 1697

    Implementation framework. by Amos Asiedu (4996946)

    Published 2025
    “…HMIS data showed statistically significant improvement in data completeness (from 62 to 87% (p < 0.001)) and decreased error rate (from 37 to 18% (p < 0.001)) after completion of the coaching visit series. …”
  18. 1698

    Study selection process. by Juan Gu (288925)

    Published 2025
    “…</p><p>Methods and analysis</p><p>We searched PubMed, Cochrane Library, Embase, and Web of Science for cohort studies published up to June 21, 2024, using relevant medical subject headings (MeSH) and keywords. …”
  19. 1699

    DHIMS2 data quality over time. by Amos Asiedu (4996946)

    Published 2025
    “…HMIS data showed statistically significant improvement in data completeness (from 62 to 87% (p < 0.001)) and decreased error rate (from 37 to 18% (p < 0.001)) after completion of the coaching visit series. …”
  20. 1700

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

    Published 2025
    “…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. …”