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significant county » significant country (Expand Search), significant amount (Expand Search), significant cluster (Expand Search)
inter decrease » linear decrease (Expand Search), water decreases (Expand Search), teer decrease (Expand Search)
mean decrease » a decrease (Expand Search)
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Showing 1 - 20 results of 14,142 for search '(( significant county based ) OR ( significant ((inter decrease) OR (mean decrease)) ))', query time: 0.49s Refine Results
  1. 1
    Intra- and inter-day precision and accuracy.

    Intra- and inter-day precision and accuracy. by Ewa Paszkowska (21246702)

    Published 2025
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  2. 2
    Data_Sheet_1_Physiological synchrony in electrodermal activity predicts decreased vigilant attention induced by sleep deprivation.docx

    Data_Sheet_1_Physiological synchrony in electrodermal activity predicts decreased vigilant attention induced by sleep deprivation.docx by Ivo V. Stuldreher (11897870)

    Published 2023
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  3. 3
    Local spatial autocorrelation analysis of the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/ngcc/ with credit to National Geomatics Center of China.

    Local spatial autocorrelation analysis of the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.... by Jiaxin Feng (4926844)

    Published 2023
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  4. 4
    Central and discrete trend changes for the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/ngcc/ with credit to National Geomatics Center of China.

    Central and discrete trend changes for the average density of living snails in Jiangling County from 2005 to 2021. The base layer of the figure in paper is from http://www.ngcc.cn/... by Jiaxin Feng (4926844)

    Published 2023
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  5. 5
    The map of the study site in Jiangling County, Hubei Province, People’s Republic of China.

    The map of the study site in Jiangling County, Hubei Province, People’s Republic of China. by Jiaxin Feng (4926844)

    Published 2023
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  6. 6
    Trends in the observed total annual rainfall and mean temperature over Taita Taveta (1981–2020).

    Trends in the observed total annual rainfall and mean temperature over Taita Taveta (1981–2020). by Francis Kibagendi Nyambariga (16425739)

    Published 2023
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  7. 7
    Analysis of kernal density for the average density of living snails in Jiangling County from 2005 to 2021.

    Analysis of kernal density for the average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  8. 8
    Significant inter-relationships between baseline variables and MSCC or MCS.

    Significant inter-relationships between baseline variables and MSCC or MCS. by Harshit Arora (22008280)

    Published 2025
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  9. 9
    Distribution of hot spot areas for the average density of living snails in Jiangling County from 2005 to 2021.

    Distribution of hot spot areas for the average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  10. 10
    Summary of the effect of MPDD on SDLP across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “-” (significant decrease)).

    Summary of the effect of MPDD on SDLP across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “-” (sign... by Mobina Faqani (22783963)

    Published 2025
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  11. 11
    Inter-assay parameters correlations.

    Inter-assay parameters correlations. by Ekaterina M. Koltsova (5464523)

    Published 2021
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  12. 12
    Summary of the effect of MPDD on ART and TIBL across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “-” (significant decrease).

    Summary of the effect of MPDD on ART and TIBL across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “... by Mobina Faqani (22783963)

    Published 2025
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  13. 13
    The number of gauging cross-sections where a statistically significant decreasing trend was identified.

    The number of gauging cross-sections where a statistically significant decreasing trend was identified. by Krzysztof Kochanek (835532)

    Published 2024
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  14. 14
    Mean decrease Gini score by Tweet and user characteristics.

    Mean decrease Gini score by Tweet and user characteristics. by Gray Babbs (16648894)

    Published 2023
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  15. 15
    Decrease of the mean number of natural teeth and POPs with age.

    Decrease of the mean number of natural teeth and POPs with age. by Sul-Hee Kim (11873853)

    Published 2021
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  16. 16
    Locations of the counties included in this study.

    Locations of the counties included in this study. by Morris Ogero (6423143)

    Published 2025
    “…Using the Optima Nutrition model, we aimed to (1) assess the impact of scaling up evidence-based nutrition interventions and (2) determine how existing resources could be optimized to reduce stunting, wasting, and anemia in children under five and anemia in pregnant women across 24 counties with the poorest nutrition outcomes.…”
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  17. 17
    The inter-regional Gini coefficient in CCD of HER and DIC.

    The inter-regional Gini coefficient in CCD of HER and DIC. by Ying Xie (50016)

    Published 2024
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  18. 18
    Differences in inter-regional synergy of HER and DIC in China.

    Differences in inter-regional synergy of HER and DIC in China. by Ying Xie (50016)

    Published 2024
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  19. 19
    Sensitivity analysis for inter-shift subscale.

    Sensitivity analysis for inter-shift subscale. by Rong Pi (21743379)

    Published 2025
    “…Studies have consistently linked occupational fatigue to decreased productivity, heightened error rates, and compromised decision-making abilities, posing significant risks to both individual nurses and healthcare organizations. …”
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  20. 20
    Crashes of older drivers in Clark County and Washoe.

    Crashes of older drivers in Clark County and Washoe. by Daiquan Xiao (12501368)

    Published 2025
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