Showing 601 - 620 results of 18,130 for search 'significantly ((((less decrease) OR (teer decrease))) OR (((we decrease) OR (a decrease))))', query time: 0.66s Refine Results
  1. 601

    Prescription data. by Dainty Ei (22265317)

    Published 2025
    “…</p><p>Conclusions</p><p>Our study demonstrated differentiated changes in psychotropic medication prescribing patterns during the COVID-19 pandemic in Sweden. We found a pandemic effect on nicotine dependence drug prescribing, which the key variables could not explain. …”
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    Raw data. by Jia Zhu (135506)

    Published 2025
    “…The remaining working conditions did not exhibit a significant difference. However, the observed decreasing trend was consistent with previously documented research. …”
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    Fig 4 - by Hyuk Sung Yoon (20208672)

    Published 2024
    Subjects:
  10. 610

    Geometric manifold comparison visualization by Eloy Geenjaar (21533195)

    Published 2025
    “…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  11. 611

    Hyperparameter ranges by Eloy Geenjaar (21533195)

    Published 2025
    “…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
  12. 612

    Convolutional vs RNN context encoder by Eloy Geenjaar (21533195)

    Published 2025
    “…While many tr-FC approaches have been proposed, most are linear approaches, e.g. computing the linear correlation at a timestep or within a window. In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
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    All data points from Fig 2. by Sara Hijazi (21656615)

    Published 2025
    “…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”
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    All data points from Fig 5. by Sara Hijazi (21656615)

    Published 2025
    “…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”
  20. 620

    All data points from Fig 8. by Sara Hijazi (21656615)

    Published 2025
    “…Specifically, we observed that demyelination caused an impairment in the ability of PV interneurons to sustain high-frequency firing associated with a substantial decrease in Kv3-specific currents. …”