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  1. 1601
  2. 1602

    Influencing factors of APCA. by Wenping Ning (19871091)

    Published 2024
    “…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”
  3. 1603

    Temporal trends in APCA. by Wenping Ning (19871091)

    Published 2024
    “…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”
  4. 1604

    Tornado diagram of one-way sensitivity analysis. by Collin Mangenah (2282995)

    Published 2025
    “…With Zvandiri, ART adherence improves, decreasing annual probability of virological failure or death. …”
  5. 1605

    Zvandiri Markov Model Parameters. by Collin Mangenah (2282995)

    Published 2025
    “…With Zvandiri, ART adherence improves, decreasing annual probability of virological failure or death. …”
  6. 1606

    Four‐state Markov model parameter inputs. by Collin Mangenah (2282995)

    Published 2025
    “…With Zvandiri, ART adherence improves, decreasing annual probability of virological failure or death. …”
  7. 1607

    Traditional Markov transfer probability matrices. by Wenping Ning (19871091)

    Published 2024
    “…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”
  8. 1608

    Spatial Markov transfer probability matrix. by Wenping Ning (19871091)

    Published 2024
    “…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”
  9. 1609

    Three-dimensional kernel density of APCA. by Wenping Ning (19871091)

    Published 2024
    “…When the spatial lag type is high-level advantage, the probability of stabilization of the low-level advantage decreases from 68.42% to 0.00%. 3) Nonfarm payrolls have the largest dampening effect at the 40% quantile.…”
  10. 1610
  11. 1611
  12. 1612
  13. 1613

    Navigation error analysis. by Haichao Li (225035)

    Published 2025
    “…The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. …”
  14. 1614

    Summary of related works. by Haichao Li (225035)

    Published 2025
    “…The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. …”
  15. 1615

    Research methodology flow diagram. by Haichao Li (225035)

    Published 2025
    “…The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. …”
  16. 1616

    Positioning error analysis. by Haichao Li (225035)

    Published 2025
    “…The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. …”
  17. 1617

    Error-Bar graph. by Haichao Li (225035)

    Published 2025
    “…The SIDFM approach ensures that only consistent LiDAR points are integrated with IMU data, reducing mismatches and improving motion estimation. SIDFM was validated using a benchmark AGV dataset and compared against baseline LiDAR-IMU fusion methods under varying acceleration conditions. …”
  18. 1618
  19. 1619

    SHAP dependence plots with interaction coloring. by Wentao Yang (205781)

    Published 2025
    “…<div><p>Objective</p><p>As an emerging insulin resistance marker, the relationship between estimated glucose disposal rate (eGDR) and frailty needs further exploration. …”
  20. 1620

    Screening process diagram. by Wentao Yang (205781)

    Published 2025
    “…<div><p>Objective</p><p>As an emerging insulin resistance marker, the relationship between estimated glucose disposal rate (eGDR) and frailty needs further exploration. …”