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Showing 81 - 100 results of 28,549 for search '(( significant ((main decrease) OR (mean decrease)) ) OR ( significant predictors based ))', query time: 0.97s Refine Results
  1. 81
    Significant (p<0.05) predictors of animal-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models.

    Significant (p<0.05) predictors of animal-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models. by Chrissie Thakwalakwa (4575547)

    Published 2020
    “…<p>Significant (p<0.05) predictors of animal-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models.…”
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  2. 82
    MyHC and actin content were decreased in DEN muscles, but not in DEX muscles.

    MyHC and actin content were decreased in DEN muscles, but not in DEX muscles. by Takashi Yamada (207878)

    Published 2019
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  3. 83
    Significant interaction (time by group) for PPTd.

    Significant interaction (time by group) for PPTd. by Einat Kodesh (13132997)

    Published 2022
    “…<p>The measurement of pain pressure threshold (mean±standard error) on the Deltoid (PPTd) showed that responders (black solid line) demonstrated a significant decrease in PPTd following eccentric exercise. …”
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  4. 84
    MANCOVA’s main and interactive effect results.

    MANCOVA’s main and interactive effect results. by Nina Brkić-Jovanović (18886883)

    Published 2024
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  5. 85
    Negative binomial relationship between sea surface temperature (SST) and daily mean point-count abundance for the six most abundant taxa with statistically significant (p<0.05) relationships across the 12 intertidal sites within the Main Hawaiian Islands from 2004–2019.

    Negative binomial relationship between sea surface temperature (SST) and daily mean point-count abundance for the six most abundant taxa with statistically significant (p<0.05) rel... by Rebecca J. Ward (9872202)

    Published 2023
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  6. 86
    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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  7. 87
    Changes in the prevalence of schistosomiasis infection in humans, livestock, and snails in Jiangling County from 2005 to 2021.

    Changes in the prevalence of schistosomiasis infection in humans, livestock, and snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  8. 88
    Global Moran’s <i>I</i> spatial autocorrelation analysis on average density of living snails in Jiangling County from 2005 to 2021.

    Global Moran’s <i>I</i> spatial autocorrelation analysis on average density of living snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  9. 89
    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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  10. 90
    Results of Joinpoint model analysis on trends of schistosomiasis-related epidemic indicators in Jiangling County from 2005 to 2021.

    Results of Joinpoint model analysis on trends of schistosomiasis-related epidemic indicators in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  11. 91
    Fig 4 -

    Fig 4 - by Jiaxin Feng (4926844)

    Published 2023
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  12. 92
    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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  13. 93
    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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  14. 94
    Investigation results of schistosomiasis in humans, livestock and investigation on snails in Jiangling County from 2005 to 2021.

    Investigation results of schistosomiasis in humans, livestock and investigation on snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  15. 95
    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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  16. 96
    Changes in the average density of living snails and the occurrence rate of frames with snails in Jiangling County from 2005 to 2021.

    Changes in the average density of living snails and the occurrence rate of frames with snails in Jiangling County from 2005 to 2021. by Jiaxin Feng (4926844)

    Published 2023
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  17. 97
    Significant (p<0.05) predictors of healthy plant-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models.

    Significant (p<0.05) predictors of healthy plant-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models. by Chrissie Thakwalakwa (4575547)

    Published 2020
    “…<p>Significant (p<0.05) predictors of healthy plant-based food groups (grams) during the dry and rainy seasons in Malawi, from multivariate models adjusted for all predictors significant (p<0.10) in univariate models.…”
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  18. 98
    Mean density (g/m<sup>2</sup>) and whole survey area fish abundance (kg) estimated using mean <i>Sa</i> and set net catch ratio.

    Mean density (g/m<sup>2</sup>) and whole survey area fish abundance (kg) estimated using mean <i>Sa</i> and set net catch ratio. by Yanhui Zhu (6697751)

    Published 2021
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  19. 99
    Predictors of rupture based on multivariate logistic regression analysis.

    Predictors of rupture based on multivariate logistic regression analysis. by Yui Kambayashi (14992697)

    Published 2023
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  20. 100
    Predictors of rupture based on multivariate logistic regression analysis.

    Predictors of rupture based on multivariate logistic regression analysis. by Yui Kambayashi (14992697)

    Published 2023
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