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learning resources » marine resources (Expand Search)
resources decrease » resources increase (Expand Search), reported decrease (Expand Search)
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
larger decrease » marked decrease (Expand Search)
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Differentially expressed genes (DEGs)<sup>a</sup> showing the greatest fold changes from each potato tissue: 10 with greatest increase in expression and 10 with greatest decrease in expression.
Published 2025“…<p>Differentially expressed genes (DEGs)<sup>a</sup> showing the greatest fold changes from each potato tissue: 10 with greatest increase in expression and 10 with greatest decrease in expression.…”
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Biases in larger populations.
Published 2025“…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. Bias decreases with increasing neurons in the population. …”
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The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness.
Published 2025“…Parameter values: interaction strengths were drawn from a half-normal distribution of zero mean and a standard deviation of 0.2, and strength for consumers was made no larger than the strength for resources. Communities started with 5 non-interacting species. …”
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Loss of ECRG4 expression decreases neutrophil mobilization from bone marrow reserves.
Published 2024Subjects: -
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Scheme of g-λ model with larger values λ.
Published 2024“…And if the value of λ assumes larger values, the distortion in the shape of the transmitted wave is associated with the plastic deformation in the uncoupled rock mass. …”
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Importance of random forest model.
Published 2025“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”
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Schematic of the Baidu SVI collection.
Published 2025“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”
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Map of the study area.
Published 2025“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”
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Research framework.
Published 2025“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”
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Perception type distribution and typical images.
Published 2025“…The results showed that: 1) the degree of coastal openness had the greatest influence on human perception while the coastal landscape with a high green visual index decreases the distinctiveness perception; 2) the random forest model can effectively predict human perception on urban coastal roads with an accuracy rate of 87% and 77%; 3) The proportion of low perception road sections with potential for improvement is 60.6%, among which the proportion of low aesthetic perception and low distinctiveness perception road sections is 10.5%. …”
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