بدائل البحث:
significantly linear » significant linear (توسيع البحث), significantly lower (توسيع البحث), significantly longer (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
significantly linear » significant linear (توسيع البحث), significantly lower (توسيع البحث), significantly longer (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
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161
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The number of gauging cross-sections where a statistically significant decreasing trend was identified.
منشور في 2024"…<p>The number of gauging cross-sections where a statistically significant decreasing trend was identified.…"
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166
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167
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168
Datasheet1_Impact of lockdown on children with type-1 diabetes: returning to the community was associated with a decrease in HbA1c.pdf
منشور في 2023"…In addition, feeling of hypoglycemia was more frequent in the patients with decreased HbA1c.</p>…"
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169
Datasheet2_Impact of lockdown on children with type-1 diabetes: returning to the community was associated with a decrease in HbA1c.pdf
منشور في 2023"…In addition, feeling of hypoglycemia was more frequent in the patients with decreased HbA1c.</p>…"
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170
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171
The Samn-Perelli Scale is a 7-point Likert scale used to assess fatigue [42, 45].
منشور في 2024الموضوعات: -
172
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Significantly variable serum amino acid and gamma-glutamyl amino acid metabolites.
منشور في 2024"…Linear mixed-effects models were used to identify serum metabolites that varied significantly among the storage conditions. …"
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177
STL Linear Combination Forecast Graph.
منشور في 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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178
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