Showing 13,421 - 13,440 results of 101,167 for search '(( 5 step decrease ) OR ( 5 ((((nn decrease) OR (a decrease))) OR (mean decrease)) ))', query time: 1.23s Refine Results
  1. 13421

    Data_Sheet_1_Determining 5HT7R’s Involvement in Modifying the Antihyperalgesic Effects of Electroacupuncture on Rats With Recurrent Migraine.pdf by Lu Liu (171341)

    Published 2021
    “…<p>Electroacupuncture (EA) is widely used in clinical practice to relieve migraine pain. 5-HT<sub>7</sub> receptor (5-HT<sub>7</sub>R) has been reported to play an excitatory role in neuronal systems and regulate hyperalgesic pain and neurogenic inflammation. 5-HT<sub>7</sub>R could influence phosphorylation of protein kinase A (PKA)- or extracellular signal-regulated kinase<sub>1</sub><sub>/</sub><sub>2</sub> (ERK<sub>1</sub><sub>/</sub><sub>2</sub>)-mediated signaling pathways, which mediate sensitization of nociceptive neurons via interacting with cyclic adenosine monophosphate (cAMP). …”
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  4. 13424

    Amygdala voxel correlations with ACC whose values <i>decrease</i> as symptoms of post-combat emotional distress increase. by Tom Brashers-Krug (762715)

    Published 2015
    “…Threshold for significance was a <i>z</i>-score < -5.39. Coronal slices through the brain at y = 4, 2, 0, -2, -4, -6, and -8 mm showing the amygdala bilaterally. …”
  5. 13425

    ACC voxel correlations with amygdala whose values <i>decrease</i> as symptoms of post-combat emotional distress increase. by Tom Brashers-Krug (762715)

    Published 2015
    “…Threshold for significance was a <i>z</i>-score < -5.39. Only values within the ACC ROI are shown. …”
  6. 13426

    Drill image dataset for training part II. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  7. 13427

    U<sup>2</sup>-Net network structure diagram [8]. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  8. 13428

    RSU-7 structure diagram [8]. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  9. 13429

    Drill image dataset for training part I. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
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  14. 13434

    Portable Visual Photoelectrochemical Biosensor Based on a MgTi<sub>2</sub>O<sub>5</sub>/CdSe Heterojunction and Reversible Electrochromic Supercapacitor for Dual-Modal Cry1Ab Prote... by Shuyun Meng (9388005)

    Published 2023
    “…In PSP, a type II MgTi<sub>2</sub>O<sub>5</sub>/CdSe heterojunction effectively drives charge separation by their cross-matched band gap structures, generating an amplified photocurrent. …”
  15. 13435

    Portable Visual Photoelectrochemical Biosensor Based on a MgTi<sub>2</sub>O<sub>5</sub>/CdSe Heterojunction and Reversible Electrochromic Supercapacitor for Dual-Modal Cry1Ab Prote... by Shuyun Meng (9388005)

    Published 2023
    “…In PSP, a type II MgTi<sub>2</sub>O<sub>5</sub>/CdSe heterojunction effectively drives charge separation by their cross-matched band gap structures, generating an amplified photocurrent. …”
  16. 13436

    Portable Visual Photoelectrochemical Biosensor Based on a MgTi<sub>2</sub>O<sub>5</sub>/CdSe Heterojunction and Reversible Electrochromic Supercapacitor for Dual-Modal Cry1Ab Prote... by Shuyun Meng (9388005)

    Published 2023
    “…In PSP, a type II MgTi<sub>2</sub>O<sub>5</sub>/CdSe heterojunction effectively drives charge separation by their cross-matched band gap structures, generating an amplified photocurrent. …”
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