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Showing 61 - 80 results of 13,265 for search '(( significantly increases decrease ) OR ( significantly greater decrease ))', query time: 0.45s Refine Results
  1. 61
    Parameters of the sliding wear test.

    Parameters of the sliding wear test. by Huashen Guan (20454677)

    Published 2024
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  2. 62
    Finite element model of shot peening.

    Finite element model of shot peening. by Huashen Guan (20454677)

    Published 2024
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  3. 63
    Chemical compositions of the 25CrNi2MoV steel (wt. %).

    Chemical compositions of the 25CrNi2MoV steel (wt. %). by Huashen Guan (20454677)

    Published 2024
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  4. 64
    Wear morphology of the SP samples: (a) (b) SP1, (c) (d) SP2, and (e)(f) SP3.

    Wear morphology of the SP samples: (a) (b) SP1, (c) (d) SP2, and (e)(f) SP3. by Huashen Guan (20454677)

    Published 2024
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  5. 65
    Average coefficient of friction of various samples.

    Average coefficient of friction of various samples. by Huashen Guan (20454677)

    Published 2024
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  6. 66
    Wear morphology of the UT sample.

    Wear morphology of the UT sample. by Huashen Guan (20454677)

    Published 2024
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  7. 67
    Residual stress of various samples: (a) surface residual stress and (b) residual stress in the depth direction.

    Residual stress of various samples: (a) surface residual stress and (b) residual stress in the depth direction. by Huashen Guan (20454677)

    Published 2024
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  8. 68
    Surface displacements after shot peening in the finite element model for different projectile diameters: (a) 0.4 mm, (b) 0.6 mm, (c) 0.8 mm, (d) 1.0 mm, and (e) surface roughness PV.

    Surface displacements after shot peening in the finite element model for different projectile diameters: (a) 0.4 mm, (b) 0.6 mm, (c) 0.8 mm, (d) 1.0 mm, and (e) surface roughness P... by Huashen Guan (20454677)

    Published 2024
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  9. 69
    Material parameters of the sample and projectile [21].

    Material parameters of the sample and projectile [21]. by Huashen Guan (20454677)

    Published 2024
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  10. 70
    Residual stress results of the finite element model: (a) comparison between surface residual stress and test values; (b) distribution along the depth direction.

    Residual stress results of the finite element model: (a) comparison between surface residual stress and test values; (b) distribution along the depth direction. by Huashen Guan (20454677)

    Published 2024
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  11. 71
    Surface roughness of various samples.

    Surface roughness of various samples. by Huashen Guan (20454677)

    Published 2024
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  12. 72
    Microstructure of various samples: (a) UT, (b) SP1, (c) SP2, and (d) SP3.

    Microstructure of various samples: (a) UT, (b) SP1, (c) SP2, and (d) SP3. by Huashen Guan (20454677)

    Published 2024
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  13. 73
    Friction coefficients of various samples: (a) UT, (b) SP1, (c) SP2, and (d) SP3.

    Friction coefficients of various samples: (a) UT, (b) SP1, (c) SP2, and (d) SP3. by Huashen Guan (20454677)

    Published 2024
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  14. 74
    Correlation analysis of the change of executive functions with the decrease of mobile phone addiction index and the increase of mindfulness level.

    Correlation analysis of the change of executive functions with the decrease of mobile phone addiction index and the increase of mindfulness level. by Jizhao Li (5856650)

    Published 2025
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  15. 75
    Comparison of the mean number of unique diagnoses per hospital admission, between 2000 and 2023, stratified by chapters of ICD-10. The table shows absolute and relative changes in the number of diagnoses, by chapter, from a total of 2.72 diagnoses per admission in 2000 to 10.43 diagnoses per admission in 2023, an increase of 284% (275%, 293%). The table also shows 95% confidence intervals and the results of a Mann-Kendall (MK) trend test as a Kendall’s tau statistic and associated two-sided p-value to identify consistently increasing or decreasing trends. All p-values have been adjusted for multiple comparisons by the Holm method.

    Comparison of the mean number of unique diagnoses per hospital admission, between 2000 and 2023, stratified by chapters of ICD-10. The table shows absolute and relative changes in... by Stuart A. Bowyer (21253319)

    Published 2025
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  16. 76
    Proportion of the increase (green) or decrease (red) in forest cover in areas with different fire recurrences in Africa, according to the Mann-Kendall test and statistically significance values.

    Proportion of the increase (green) or decrease (red) in forest cover in areas with different fire recurrences in Africa, according to the Mann-Kendall test and statistically significance values. by Oswaldo Maillard (20660661)

    Published 2025
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  17. 77
    Join-point regression analysis of the statistically significant linear increase in use of antidepressants during the observed time period.

    Join-point regression analysis of the statistically significant linear increase in use of antidepressants during the observed time period. by Jelena Filimonovic (22305307)

    Published 2025
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  18. 78
    Differentially expressed genes (DEGs) exhibiting both increased and decreased expression levels.

    Differentially expressed genes (DEGs) exhibiting both increased and decreased expression levels. by Liwen Wang (276995)

    Published 2025
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  19. 79
    Significantly Enriched Pathways.

    Significantly Enriched Pathways. by Jiyong Zhang (2498740)

    Published 2025
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  20. 80
    Model-averaged coefficients, significance, and relative importance (RI) of the predictor variables for the GLMMs to evaluate effects on: (A) overall pollinator abundance; (B) fruit production per female tree, (C) seed production per female tree; and (D) seed weight. Farming system refers to ecological vs. conventional practices; CCA1 refers to the first axis of the CCA and depicts the relationship between the % of natural habitats in the landscape and the composition of the pollinator community (increase abundance of wild bees with the increase in natural habitats); Male-to-female ratio and Male-to-female ratio<sup>2</sup> indicate linear and quadratic terms, respectively. Significant <i>p</i>-values are marked in bold. RI was estimated by summing the Akaike weights over all the models where each explanatory variable appeared, and highlights the importance of these variables in the models [75].

    Model-averaged coefficients, significance, and relative importance (RI) of the predictor variables for the GLMMs to evaluate effects on: (A) overall pollinator abundance; (B) fruit... by Carmelo Gómez-Martínez (9384385)

    Published 2025
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