Showing 181 - 200 results of 18,170 for search '(( significantly ((we decrease) OR (a decrease)) ) OR ( significant linear decrease ))', query time: 0.41s Refine Results
  1. 181

    Logistic regression for LSES population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  2. 182

    Logistic regression for HSES population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  3. 183

    Logistic regression for overall population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  4. 184

    BMISES_Data_Part1. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  5. 185

    Baseline characteristics of HSES/LSES population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  6. 186

    Baseline characteristics of overall population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  7. 187

    Diagram of study population. by Krystal Hunter (6820052)

    Published 2025
    “…BMI was a significant factor in PTB for lower socioeconomic status (LSES) women. …”
  8. 188

    Geometric manifold comparison visualization by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  9. 189

    Hyperparameter ranges by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  10. 190

    Convolutional vs RNN context encoder by Eloy Geenjaar (21533195)

    Published 2025
    “…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  11. 191
  12. 192

    DataSheet1_Pharmacological inhibition of receptor protein tyrosine phosphatase β/ζ decreases Aβ plaques and neuroinflammation in the hippocampus of APP/PS1 mice.docx by Teresa Fontán-Baselga (20392470)

    Published 2024
    “…In addition, we observed a significant decrease in the number and size of astrocytes in both sexes and in the number of microglial cells in a sex-dependent manner. …”
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  16. 196

    <b>Manure improves temperature sensitivity of soil organic carbon by increasing soil alphaproteobacteria, phenols, and pH and decreasing soil esters</b> by Andong Cai (5237024)

    Published 2024
    “…<a href="" target="_blank">There was a positive linear relationship between the Q<sub>10</sub> and SOC</a>, which implied a negative feedback of manure-increased SOC to future warming. …”
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  19. 199

    Supplementary file 1_Intercropping of short- and tall-stature maize decreases lodging risk without yield penalty at high planting density.docx by Jianhong Ren (2186293)

    Published 2025
    “…Lodging rate of sole XY under normal and high density was 4.3% and 22.0% in 2021, but lodging was absent for ZD and intercropped XY, which demonstrated that the lodging resistance of intercropped XY was significantly enhanced. This study presents a strategy to enhance maize lodging resistance without yield penalty or requiring additional inputs.…”
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