Search alternatives:
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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1681
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1682
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1683
Ethogram describing all outcome measures.
Published 2024“…Apathetic animals are hypothesised to show a decreased interest in stimuli of all valences, whereas depressed animals are thought to be less interested in positive stimuli only, due to anhedonia, a key symptom of depression. …”
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1684
Flow chart of animal experiment.
Published 2025“…Then, we evaluated the effects of PMSC intervention on POI rats: Compared to the untreated MOD group, the estrous cycle of rats in the PMSC group gradually became regular, the ovarian weight and ovarian index were significantly increased, and the ovarian tissue structure was improved by showing an increase in the number of follicles and a decrease in the number of atretic follicles. …”
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1685
Primers used in present study.
Published 2025“…Interleukin-10 levels were significantly elevated in all treatments except in the positive control (+ve A0). …”
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1686
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1687
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1688
Design of the D-trial.
Published 2024“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
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1689
Estimated mean values for light interception.
Published 2024“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
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1690
Raw data V-trial.
Published 2024“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
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1691
Raw data D-trial.
Published 2024“…Empirical models for the relationships between the investigated plant traits and PD/DVP were created using linear regression analysis preceded by a lack-of-fit test. An increase in PD led to a linear decrease in inflorescence yield per plant (<i>p</i> = 0.02), whereas a positive linear relationship was found for inflorescence yield (<i>p</i> = 0.0001) and CBD yield (<i>p</i> = 0.0002) per m<sup>2</sup>. …”
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1692
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1693
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1694
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1695
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1696
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1697
Detailed information of the observation datasets.
Published 2025“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
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1698
General technical specification for GW154/6700.
Published 2025“…On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
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1699
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1700