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significantly affect » significantly affected (Expand Search), significant effect (Expand Search), significant effects (Expand Search)
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Showing 1 - 20 results of 15,569 for search '(( significant spatial decrease ) OR ( significantly affect decrease ))', query time: 0.46s Refine Results
  1. 1
    Spatial distribution of NPP trend and significance of NPP trend in Anhui from 2001 to 2020.

    Spatial distribution of NPP trend and significance of NPP trend in Anhui from 2001 to 2020. by Huan Tang (334333)

    Published 2024
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  2. 2
    Significant clusters: Coronal PET images showing brain regions with significant (p < 0.001 and K > 50) metabolic inhibition (A-G) and activation (H-I) in rats following cocaine self-administration.

    Significant clusters: Coronal PET images showing brain regions with significant (p < 0.001 and K > 50) metabolic inhibition (A-G) and activation (H-I) in rats following cocaine sel... by Christopher Rowan (21499924)

    Published 2025
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  3. 3
    Pixel-wise trends in annual time series data of NDVI and Tmin during 1982 to 2015 (a) Sen’s slope of NDVI (b) p-values of NDVI, (c)significant trends (p<0.05) in average annual slope (p<0.01) of NDVI and (d) significant trends in annual average slope (p<0.05) of Tmin.

    Pixel-wise trends in annual time series data of NDVI and Tmin during 1982 to 2015 (a) Sen’s slope of NDVI (b) p-values of NDVI, (c)significant trends (p<0.05) in average annual slo... by Jamal Hassan Ougahi (13513875)

    Published 2022
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  4. 4
    Spatial models.

    Spatial models. by Qian Chen (18883)

    Published 2023
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  5. 5
    Increasing and decreasing temperature trends in <i>M</i>. <i>peregrina</i> habitats at 95% confidence level.

    Increasing and decreasing temperature trends in <i>M</i>. <i>peregrina</i> habitats at 95% confidence level. by Hossein Piri Sahragard (19226096)

    Published 2024
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  6. 6
    Provincial spatial distribution of physical capital in 2019.

    Provincial spatial distribution of physical capital in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  7. 7
    Provincial spatial distribution of subjective poverty in 2019.

    Provincial spatial distribution of subjective poverty in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  8. 8
    Provincial spatial distribution of human capital in 2019.

    Provincial spatial distribution of human capital in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  9. 9
    Provincial spatial distribution of social capital in 2019.

    Provincial spatial distribution of social capital in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  10. 10
    Provincial spatial distribution of financial capital in 2019.

    Provincial spatial distribution of financial capital in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  11. 11
    Provincial spatial distribution of public service supply in 2019.

    Provincial spatial distribution of public service supply in 2019. by Yuanquan Lu (17125093)

    Published 2023
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  12. 12
    Change trend of regression coefficient of factors affecting ozone concentration.

    Change trend of regression coefficient of factors affecting ozone concentration. by Li-Min Wang (783263)

    Published 2024
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  13. 13
    Spatial exploration patterns of tumor bearing mice under different treatment conditions in the Morris Water Maze (MWM).

    Spatial exploration patterns of tumor bearing mice under different treatment conditions in the Morris Water Maze (MWM). by Robert Botelho (20308297)

    Published 2024
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  14. 14
    Tract-based spatial statistics analyses identified white matter areas affected by a significant decrease in fractional anisotropy (FA) in patients with psychotic bipolar disorder (PBD) (N = 29), non-psychotic bipolar disorder (NPBD) (N = 23), and bipolar disorder (BD) (N = 52) in comparisons with healthy controls (HCs) (N = 65).

    Tract-based spatial statistics analyses identified white matter areas affected by a significant decrease in fractional anisotropy (FA) in patients with psychotic bipolar disorder (PBD) (N = 29), non-psychotic bipolar disorder (NPBD) (N = 23), and bipolar disorder (BD) (N = 52) in comparisons with healthy controls (HCs) (N = 65). by Dong-Kyun Lee (497757)

    Published 2022
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  15. 15
    Spatial exploration patterns of non-tumor bearing mice under different treatment conditions in the Morris Water Maze (MWM).

    Spatial exploration patterns of non-tumor bearing mice under different treatment conditions in the Morris Water Maze (MWM). by Robert Botelho (20308297)

    Published 2024
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  16. 16
    Distribution of regression coefficients of factors affecting ozone from 2015 to 2019.

    Distribution of regression coefficients of factors affecting ozone from 2015 to 2019. by Li-Min Wang (783263)

    Published 2024
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  17. 17
    Spatial distribution of average annual NDVI (a), precipitation (b), Tmin (c) and Tmax (d) over the UJRB during 1982 to 2015.

    Spatial distribution of average annual NDVI (a), precipitation (b), Tmin (c) and Tmax (d) over the UJRB during 1982 to 2015. by Jamal Hassan Ougahi (13513875)

    Published 2022
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  18. 18
    Brain regions with significant metabolic inhibition (p < 0.001, K = 50) (A) and activation (B) in rats following cocaine self-administration compared to baseline. Cluster location is both noted and indicated by coordinates in stereotaxic space (medial-lateral, anterior-posterior, and dorsal-ventral). The t-value and Z-scores were calculated from the average BGluM of all voxels within the significant clusters. KE represents the number of voxels in the respective clusters. Each cell under “Brain Region” represents a separate cluster.

    Brain regions with significant metabolic inhibition (p < 0.001, K = 50) (A) and activation (B) in rats following cocaine self-administration compared to baseline. Cluster location... by Christopher Rowan (21499924)

    Published 2025
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  19. 19
    Annual Mann-Kendall trend statistics calculated from spatially averaged data of NDVI, precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) for each vegetation type during 1982 to 2015.

    Annual Mann-Kendall trend statistics calculated from spatially averaged data of NDVI, precipitation, maximum temperature (Tmax) and minimum temperature (Tmin) for each vegetation t... by Jamal Hassan Ougahi (13513875)

    Published 2022
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  20. 20
    Seasonal Mann-Kendall trend statistics calculated from spatially averaged data over the whole UJRB and each vegetation class in four quarters (Q1, Q2, Q3 and Q4) during 1982 to 2013.

    Seasonal Mann-Kendall trend statistics calculated from spatially averaged data over the whole UJRB and each vegetation class in four quarters (Q1, Q2, Q3 and Q4) during 1982 to 201... by Jamal Hassan Ougahi (13513875)

    Published 2022
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