Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
linear decrease » linear increase (Expand Search)
range increase » large increases (Expand Search), rapid increase (Expand Search), rate increased (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
linear decrease » linear increase (Expand Search)
range increase » large increases (Expand Search), rapid increase (Expand Search), rate increased (Expand Search)
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Metabolites with decreasing levels during the development.
Published 2025“…<p>Temporal profiles of polar metabolites and lipids with SCN levels significantly decreasing from E19 to P28. Rhythmicity was determined by eJTK; full or dashed lines depict the profiles that either did or did not pass the significance threshold (FDR-adjusted <i>P</i> < 0.05), respectively.…”
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Image1_Association between mental health and male fertility: depression, rather than anxiety, is linked to decreased semen quality.tif
Published 2024“…</p>Results<p>Status of depression was negatively associated with semen quality parameters, whereas no statistically significant association was recognized between anxiety and semen quality except that sperm concentration was decreased by 25.60 (95% CI, 1.226 to 49.965, P=0.040) ×10<sup>6</sup>/ml in moderate to severe anxiety group referring to normal group. …”
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Temperature-invariant parameters, symbols, ranges and baseline values, and sources.
Published 2025Subjects: -
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Temperature-dependent parameters, symbols, derived curves, ranges, and their sources.
Published 2025Subjects: -
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The variables that significantly predicted litter clump weight in shelter cats.
Published 2025“…D) Greater food consumption was significantly related to increased litter clump weight (p = 0.039). …”
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STL Linear Combination Forecast Graph.
Published 2025“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”
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