Search alternatives:
largest decrease » largest decreases (Expand Search), larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
latent decrease » latency decreased (Expand Search), content decreased (Expand Search), greatest decrease (Expand Search)
mean decrease » a decrease (Expand Search)
largest decrease » largest decreases (Expand Search), larger decrease (Expand Search), marked decrease (Expand Search)
linear decrease » linear increase (Expand Search)
latent decrease » latency decreased (Expand Search), content decreased (Expand Search), greatest decrease (Expand Search)
mean decrease » a decrease (Expand Search)
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Table_1_Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010–2019 in Lanzhou, China.DOCX
Published 2022“…An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (−4.75% to −1.46%) decrease in the weekly influenza case counts in a low RH environment. …”
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Confirmation of microarray findings with RT-qPCR.
Published 2015“…<p>(A) Three genes from the focal adhesion, cytoskeleton and ECM gene set (Lamc1, Dock1 and Thbs2) were selected and confirmed to be decreased 6hr following adipogenic induction in FTO knock-down cells. …”
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Flowchart of CNNBLSTM algorithm.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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Comparison of TL and VL of different algorithms.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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13450
Analysis of ST characteristics of TF.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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Schematic diagram of STTFP model.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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Summary of the methods in current research.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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Diagram of the improved CNNBLSTM model.
Published 2025“…Compared with the traditional convolutional neural network with bidirectional long short-term memory algorithm, the training loss decreased by 42.86% The suggested algorithm outperformed the current advanced algorithms in terms of prediction precision, with an average absolute percentage error of 0.233 and a root mean square error of 23.87. …”
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Source dataset and code: <b>Feeding specialization shapes functional diversity of avian assemblages along a tropical rainforest elevational gradient</b>
Published 2025“…</p><p dir="ltr">Standardized functional richness declined sharply from the lowlands to 1700 m a.s.l., followed by a weak decrease towards the treeline. …”
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13460