Search alternatives:
linear decrease » linear increase (Expand Search)
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
linear decrease » linear increase (Expand Search)
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
-
2461
-
2462
-
2463
-
2464
Prescription data.
Published 2025“…Despite less restrictive measures in the first stage of the pandemic, Sweden experienced significant mental health consequences and changes in psychotropic medication prescribing.…”
-
2465
-
2466
-
2467
-
2468
-
2469
-
2470
-
2471
Comparison of absolute and relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
-
2472
Rate of convergence for relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
-
2473
Ultrafine Particulate Matter Exacerbates the Risk of Delayed Neural Differentiation: Modulation Role of METTL3-Mediated m<sup>6</sup>A Modification
Published 2025“…By employing <i>N</i>6-methyladenosine (m<sup>6</sup>A) methylated RNA immunoprecipitation sequencing and bioinformatics, we identified <i>Zic1</i> as a key target of PM<sub>0.1</sub>-induced developmental disturbances. …”
-
2474
-
2475
-
2476
-
2477
-
2478
-
2479
A Comparison of Pediatric Prehospital Opioid Encounters and Social Vulnerability
Published 2024“…The analysis demonstrated that as socioeconomic status (SES) improves, the likelihood of opioid-related activations increases significantly supported by a significant negative linear trend (Estimate = −0.2971, SE = 0.1172, z = −2.54, <i>p</i> = 0.0112. …”
-
2480
Complexity comparison of different models.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”