Search alternatives:
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
values decrease » values increased (Expand Search), largest decrease (Expand Search)
larger decrease » marked decrease (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
values decrease » values increased (Expand Search), largest decrease (Expand Search)
larger decrease » marked decrease (Expand Search)
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<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>"
Published 2025“…The locomotion values (traces and metrics) are in arbitrary units with larger integers representing a greater displacement of the spherical treadmill, the hemodynamic (Hbt) values (traces and metrics) are a percentage change from the normalised baseline (prior to stimulus presentation), and the corresponding time series vector is presented in seconds. …”
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Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively....
Published 2025“…The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively. …”
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CM-DWM-EC chart using 30% decrease in the mean for the E(KeV).
Published 2024“…<p>CM-DWM-EC chart using 30% decrease in the mean for the E(KeV).</p>…”
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ROC curve and AUC value of all models.
Published 2024“…As for Specificity (82.94%) and ROC-AUC (82.13%), the Multilayer Perceptron with SGD optimizer obtained the highest scores. …”
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Claudin V is decreased following infection with Mtb.
Published 2024“…Exposure to Mtb H37Rv and HN878 decreased claudin V expression compared to uninfected controls in the frontal cortex (E), cerebral nuclei (J), brain stem (O), thalamus (T), and hippocampus (Y). …”
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AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre
Published 2025“…To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”
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