Showing 1 - 20 results of 108 for search '(( significantly ((we decrease) OR (greater decrease)) ) OR ( significant factors decrease ))~', query time: 0.50s Refine Results
  1. 1

    Assessing Bivalves as Biomonitors of Per- and Polyfluoroalkyl Substances in Coastal Environments by Shannon E. Jones (17558652)

    Published 2025
    “…The isomer distribution and precursor-to-terminal compound ratios provide compelling evidence that the biotransformation of PFAS precursors likely drives these elevated factors. Additionally, the bioaccumulation factors of PFAS decrease with increasing organism size and age, suggesting that smaller and younger bivalves have greater bioaccumulation potential and are more susceptible to PFAS contamination. …”
  2. 2

    Mortality dataset used in analysis. by Samuel Sendagala (21417164)

    Published 2025
    “…We determined the mortality rate and associated risk factors among infants exposed and not exposed to HIV attending immunization clinics in Uganda.…”
  3. 3

    Datasets used in the study. by Rajon Banik (12066099)

    Published 2025
    “…</p><p>Objectives</p><p>The objective of this study was to assess the changes in the availability and readiness of health facilities to provide modern family planning services in Bangladesh between 2014 and 2017, and identify factors associated with facility readiness.</p><p>Methods</p><p>We performed a secondary analysis of cross-sectional data from Bangladesh Health Facility Surveys (BHFS) conducted in 2014 and 2017. …”
  4. 4

    Results of RF algorithm screening factors. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  5. 5

    Experimental design of this study. by Renya Kawakami (20469088)

    Published 2024
    “…For example, several empirical and theoretical studies have demonstrated that older males make greater investment in reproduction compared with younger males. …”
  6. 6

    All relevant data of this study. by Renya Kawakami (20469088)

    Published 2024
    “…For example, several empirical and theoretical studies have demonstrated that older males make greater investment in reproduction compared with younger males. …”
  7. 7

    Row data. by Xiangyu Wang (341093)

    Published 2025
    “…Moreover, Life Sciences & Medicine students demonstrated a greater tendency toward negative self-perception, low psychological well-being level, and decreased creative self-efficacy, compared to peers in other disciplines.…”
  8. 8

    Univariate linear regression analysis of scales. by Xiangyu Wang (341093)

    Published 2025
    “…Moreover, Life Sciences & Medicine students demonstrated a greater tendency toward negative self-perception, low psychological well-being level, and decreased creative self-efficacy, compared to peers in other disciplines.…”
  9. 9

    Major hyperparameters of RF-SVR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  10. 10

    Pseudo code for coupling model execution process. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  11. 11

    Major hyperparameters of RF-MLPR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  12. 12

    Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

    Published 2024
    “…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”
  13. 13

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

    Published 2025
    “…The results showed that malaria incidence decreased with greater variance across Tanzania. Mean malaria incidence decreased from 0.347 (95% CI: 0.336, 0.357) in 2000 to 0.118 (95% CI: 0.114, 0.122) in 2020, relative to the increasing insecticide-treated bednets (ITNs) coverage (0.037; 95% CI: 0.036, 0.039 in 2000 to 0.496; 95% CI: 0.476, 0.517 in 2020). …”
  14. 14

    Table 1_Effects of grassland degradation on soil ecological stoichiometry and soil microbial community on the South of the Greater Khingan Mountains.docx by Yuyu Li (3939137)

    Published 2024
    “…Improved understanding of soil and microbial community diversity during meadow steppe degradation is crucial for predicting degradation mechanisms and restoration strategies. Here, we used Illumina sequencing technology to investigate the patterns of soil microbial community structure and the driving factors of its change across different degradation degrees of meadow steppe [i.e., non-degraded grasslands (NDG), lightly degraded grasslands (LDG), moderately degraded grasslands (MDG), and severely degraded grasslands (SDG)] south of the Greater Khingan Mountains. …”
  15. 15

    Presentation1_Leaf nutrient traits exhibit greater environmental plasticity compared to resource utilization traits along an elevational gradient.zip by Xing Zhang (11943)

    Published 2024
    “…Generally, as elevation increased, SLA decreased, while LDMC significantly increased (P < 0.001), and LN first increase and then decreased (P < 0.001). …”
  16. 16

    Table1_Leaf nutrient traits exhibit greater environmental plasticity compared to resource utilization traits along an elevational gradient.xlsx by Xing Zhang (11943)

    Published 2024
    “…Generally, as elevation increased, SLA decreased, while LDMC significantly increased (P < 0.001), and LN first increase and then decreased (P < 0.001). …”
  17. 17

    Participant characteristics by village. by Tyler M. Barrett (20846174)

    Published 2025
    “…We hypothesized that farmers with greater market-based wealth and more farming experience would have higher odds of adaptation. …”
  18. 18

    Supplementary information–dataset. by Leriana Garcia Reis (12646978)

    Published 2024
    “…HF diet and light treatment increased fecal corticosterone output (P<0.05) during lactation. Dams exhibited significant 12 h and 24 h rhythms of activity out of the nest in the first 48 h postnatal, with time outside of the nest greater in the second 24 h period. …”
  19. 19

    Experimental timeline overview. by Leriana Garcia Reis (12646978)

    Published 2024
    “…HF diet and light treatment increased fecal corticosterone output (P<0.05) during lactation. Dams exhibited significant 12 h and 24 h rhythms of activity out of the nest in the first 48 h postnatal, with time outside of the nest greater in the second 24 h period. …”
  20. 20

    Climate is more influential to vegetation green-up than factors that contribute to erosion following high-severity wildfire by Joseph Crockett (22077659)

    Published 2025
    “…In <a>highly erodible</a> scenarios, when accounting for growing season climate, coefficient of variation for year-of-fire precipitation, total precipitation, and soil erodibility decreased greenness in the fifth year. While the effects of year-of-fire factors related to erosion were significant, they were small, and the variability explained by growing season vapor pressure deficit and growing season precipitation were significantly greater.…”