Showing 1,401 - 1,420 results of 99,640 for search '(( 5 ((step decrease) OR (teer decrease)) ) OR ( 5 ((a decrease) OR (nn decrease)) ))', query time: 1.28s Refine Results
  1. 1401

    Extremely Soft, Stretchable, and Self-Adhesive Silicone Conductive Elastomer Composites Enabled by a Molecular Lubricating Effect by Jin Huang (146235)

    Published 2022
    “…The resultant SF-C-PDMS not only exhibits superior softness but also can readily recover after a strain of 1000%. The initial resistance only decreases by 8% after 100000 cycles of tensile fatigue test (100% strain, 0.5 Hz, 15 mm/s). …”
  2. 1402

    Extremely Soft, Stretchable, and Self-Adhesive Silicone Conductive Elastomer Composites Enabled by a Molecular Lubricating Effect by Jin Huang (146235)

    Published 2022
    “…The resultant SF-C-PDMS not only exhibits superior softness but also can readily recover after a strain of 1000%. The initial resistance only decreases by 8% after 100000 cycles of tensile fatigue test (100% strain, 0.5 Hz, 15 mm/s). …”
  3. 1403

    Extremely Soft, Stretchable, and Self-Adhesive Silicone Conductive Elastomer Composites Enabled by a Molecular Lubricating Effect by Jin Huang (146235)

    Published 2022
    “…The resultant SF-C-PDMS not only exhibits superior softness but also can readily recover after a strain of 1000%. The initial resistance only decreases by 8% after 100000 cycles of tensile fatigue test (100% strain, 0.5 Hz, 15 mm/s). …”
  4. 1404

    Extremely Soft, Stretchable, and Self-Adhesive Silicone Conductive Elastomer Composites Enabled by a Molecular Lubricating Effect by Jin Huang (146235)

    Published 2022
    “…The resultant SF-C-PDMS not only exhibits superior softness but also can readily recover after a strain of 1000%. The initial resistance only decreases by 8% after 100000 cycles of tensile fatigue test (100% strain, 0.5 Hz, 15 mm/s). …”
  5. 1405

    Extremely Soft, Stretchable, and Self-Adhesive Silicone Conductive Elastomer Composites Enabled by a Molecular Lubricating Effect by Jin Huang (146235)

    Published 2022
    “…The resultant SF-C-PDMS not only exhibits superior softness but also can readily recover after a strain of 1000%. The initial resistance only decreases by 8% after 100000 cycles of tensile fatigue test (100% strain, 0.5 Hz, 15 mm/s). …”
  6. 1406
  7. 1407

    Syntheses of Pentanuclear Group 6 Iridium Clusters by Core Expansion of Tetranuclear Clusters with Ir(CO)<sub>2</sub>(η<sup>5</sup>‑C<sub>5</sub>Me<sub>4</sub>R) (R = H, Me) by Michael D. Randles (1902586)

    Published 2013
    “…Single-crystal X-ray diffraction studies of <b>1a</b>–<b>1d</b>, <b>2</b>, <b>3a</b>–<b>3d</b>, and <b>4</b> confirmed their molecular structures, including the μ-η<sup>1</sup>:η<sup>5</sup>-CH<sub>2</sub>C<sub>5</sub>Me<sub>4</sub> ligand at hydrido cluster <b>2</b>, derived from a C–H bond activation of one of the methyl groups. …”
  8. 1408

    Trypanosome locomotion with a decreased body stiffness of , which leads to an increase in both the swimming velocity and rotation frequency when compared to the reference case in S1V. by Florian A. Overberg (21402904)

    Published 2025
    “…<p>Trypanosome locomotion with a decreased body stiffness of , which leads to an increase in both the swimming velocity and rotation frequency when compared to the reference case in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013111#pcbi.1013111.s003" target="_blank">S1V</a>.…”
  9. 1409

    The prediction result is displayed on the hotel dataset, which includes the training procedure when the loss function is decreased and the model saved with training rounds as a multiple of five. by Hongxia Wang (241142)

    Published 2025
    “…<p>The prediction result is displayed on the hotel dataset, which includes the training procedure when the loss function is decreased and the model saved with training rounds as a multiple of five.…”
  10. 1410
  11. 1411

    Image5_Repression of enhancer RNA PHLDA1 promotes tumorigenesis and progression of Ewing sarcoma via decreasing infiltrating T‐lymphocytes: A bioinformatic analysis.TIF by Runzhi Huang (7428713)

    Published 2022
    “…External validation based on multidimensional online databases and scRNA-seq analysis were used to verify our key findings.</p><p>Results: A six-different-dimension regulatory network was constructed based on 17 DEeRNAs, 29 DETFs, 9 DETGs, 5 immune cells, 24 immune gene sets, and 8 hallmarks of cancer. …”
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