Showing 1,421 - 1,440 results of 6,770 for search 'significantly ((less decrease) OR (we decrease))', query time: 0.36s Refine Results
  1. 1421

    Single agent and multi-agents tasks for <i>LazyAct</i>. by Hongjie Zhang (136127)

    Published 2025
    “…The inferences reduction significantly decreases the time and FLOPs required by the <i>LazyAct</i> algorithm to complete tasks. …”
  2. 1422

    Network architectures for multi-agents task. by Hongjie Zhang (136127)

    Published 2025
    “…The inferences reduction significantly decreases the time and FLOPs required by the <i>LazyAct</i> algorithm to complete tasks. …”
  3. 1423

    Primers for RT-qPCR. by Jiaoyang Li (2862269)

    Published 2024
    “…To elucidate the function of NSP2 during PRRSV infection, we identified SH3KBP1 as an NSP2-interacting host protein using mass spectrometry. …”
  4. 1424

    LC_MS/MS analysis for OGG1 interactomes. by Lang Pan (5145221)

    Published 2024
    “…Importantly, inhibiting OGG1’s ability to recognize 8-oxoGua significantly decreases RSV progeny production. Our results underscore the viral replication machinery’s adaptation to oxidative challenges, suggesting that inhibiting OGG1’s reading function could be a novel strategy for antiviral intervention.…”
  5. 1425

    Primer sequences for RT q-PCR. by Lang Pan (5145221)

    Published 2024
    “…Importantly, inhibiting OGG1’s ability to recognize 8-oxoGua significantly decreases RSV progeny production. Our results underscore the viral replication machinery’s adaptation to oxidative challenges, suggesting that inhibiting OGG1’s reading function could be a novel strategy for antiviral intervention.…”
  6. 1426

    Oligo sequences for EMSA and excision assay. by Lang Pan (5145221)

    Published 2024
    “…Importantly, inhibiting OGG1’s ability to recognize 8-oxoGua significantly decreases RSV progeny production. Our results underscore the viral replication machinery’s adaptation to oxidative challenges, suggesting that inhibiting OGG1’s reading function could be a novel strategy for antiviral intervention.…”
  7. 1427

    Antibodies used in this study. by Kevin J. Kokesh (19859571)

    Published 2024
    “…Taken together, MARCKS protein is upregulated in CF cells and there is decreased phosphorylation of the protein due to a decrease in PKC activity and presumably increased cathepsin B mediated proteolysis of the protein after <i>M</i>. …”
  8. 1428

    Time and flowrate used for proteomics. by Kevin J. Kokesh (19859571)

    Published 2024
    “…Taken together, MARCKS protein is upregulated in CF cells and there is decreased phosphorylation of the protein due to a decrease in PKC activity and presumably increased cathepsin B mediated proteolysis of the protein after <i>M</i>. …”
  9. 1429

    S1 Graphical abstract - by Kevin J. Kokesh (19859571)

    Published 2024
    “…Taken together, MARCKS protein is upregulated in CF cells and there is decreased phosphorylation of the protein due to a decrease in PKC activity and presumably increased cathepsin B mediated proteolysis of the protein after <i>M</i>. …”
  10. 1430
  11. 1431

    Mean parameter values for the selected crops. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  12. 1432

    Performance comparison of ML models. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  13. 1433

    Comparative data of different soil samples. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  14. 1434

    Confusion matrix of random forest model. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  15. 1435

    Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  16. 1436

    Evaluation metrics of selected ML models. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  17. 1437

    Block diagram of the proposed system. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  18. 1438

    Chart for applicable amount of fertilizers. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  19. 1439

    Cost analysis of irrigation controller unit. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”
  20. 1440

    Run times of two algorithms. by Gourab Saha (8987405)

    Published 2025
    “…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”