Search alternatives:
greater decrease » greater increase (Expand Search), greater increases (Expand Search), rate decreased (Expand Search)
largest decrease » largest decreases (Expand Search), larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
mean decrease » a decrease (Expand Search)
greater decrease » greater increase (Expand Search), greater increases (Expand Search), rate decreased (Expand Search)
largest decrease » largest decreases (Expand Search), larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
mean decrease » a decrease (Expand Search)
-
10061
-
10062
-
10063
-
10064
-
10065
Knockdown of MUC16 results in decreased tight junction function and ZO-1/occludin expression, whereas knockdown of MUC1 has no effect on tight junctions.
Published 2014“…<p>(A) Immunofluorescence analysis of occludin localization demonstrated normal linear distribution of occludin in the MUC16 scrambled control (scr16) cells (A) as compared to the disrupted localization seen in the shMUC16 cells (B). …”
-
10066
Drying Contraction Assessment of Ceramic Products Produced by Extrusion or Pressing Formulated with Sheep Wool Waste
Published 2018“…<div><p>The main aim of this paper was to evaluate ceramic products containing a percentage of ash from sheep wool waste through drying linear shrinkage from a small brickyard in Bagé - RS. …”
-
10067
-
10068
-
10069
-
10070
Assessment values of machine learning models.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
-
10071
List of datasets in AqSolDB.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
-
10072
Feature importance derived from SHAP analysis.
Published 2025“…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …”
-
10073
-
10074
-
10075
Significant repeated measurements sEMG outcomes.
Published 2025“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”
-
10076
Maximum voluntary contraction assessment.
Published 2025“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”
-
10077
Significant single measurement sEMG outcomes.
Published 2025“…<div><p>Lateral ankle sprain (LAS) is a very common injury in the world of basketball. …”
-
10078
-
10079
DataSheet1_Decreasing incidence and mortality of lung cancer in Hungary between 2011 and 2021 revealed by robust estimates reconciling multiple data sources.ZIP
Published 2024“…The COVID-19 pandemic resulted in a statistically significant decrease in lung cancer incidence, especially in the 50–59 age group (both sexes).…”
-
10080
Image_3_Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations.TIF
Published 2022“…<p>Large plant breeding populations are traditionally a source of novel allelic diversity and are at the core of selection efforts for elite material. …”