Showing 18,681 - 18,700 results of 21,342 for search '(( significance ((a decrease) OR (step decrease)) ) OR ( significant decrease decrease ))', query time: 0.59s Refine Results
  1. 18681

    Data Sheet 1_Integrative analysis of DNA methylation, RNA sequencing, and genomic variants in the cancer genome atlas (TCGA) to predict endometrial cancer recurrence.zip by Jin Hwa Hong (6523928)

    Published 2025
    “…These were visualized through volcano plots and heat maps, while decision trees and random forests classified and stratified the samples.</p>Results<p>A machine learning analysis combined with box plots showed that in the copy number-high (CN-H) recurrence group, PARD6G-AS1 had decreased methylation, CSMD1 had increased methylation, and TESC expression was higher than the non-recurrence group. …”
  2. 18682

    Comparison results of ablation experiments. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  3. 18683

    DataSheet4_Deficiency of autism susceptibility gene Trio in cerebellar Purkinje cells leads to delayed motor impairments.zip by Jinxin Wang (1696837)

    Published 2025
    “…<p>Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by social interaction deficits, restricted interests and repetitive behaviors. …”
  4. 18684

    Spato-temporal changes in land use types. by Chao Ma (207385)

    Published 2025
    “…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. …”
  5. 18685

    Table of dataset division. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  6. 18686

    DataSheet5_Deficiency of autism susceptibility gene Trio in cerebellar Purkinje cells leads to delayed motor impairments.zip by Jinxin Wang (1696837)

    Published 2025
    “…<p>Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by social interaction deficits, restricted interests and repetitive behaviors. …”
  7. 18687

    Pattern indices of landscape levels. by Chao Ma (207385)

    Published 2025
    “…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. …”
  8. 18688

    Table 1_MicroRNA-27b alleviates septic cardiomyopathy by targeting the Mff/MAVS axis.docx by Xincai Wang (7819064)

    Published 2025
    “…</p>Results<p>Bioinformatics analysis revealed significant downregulation of miR-27b in SCM cardiac tissues (log2FC=-3.9, P<0.001). …”
  9. 18689

    Striking image. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  10. 18690

    Flow chart. by Aysenur Karakus (21192337)

    Published 2025
    “…Both TTH and migraine groups received PRT twice a week for six weeks,</p><p>Results</p><p>Within-group comparisons showed significant decreases in attack frequency, VAS, HIT-6, PCS, and WHODAS-II scores in both groups post-intervention (p<0.001). …”
  11. 18691

    Precision, recall, F1-Score curve. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  12. 18692

    DataSheet1_Deficiency of autism susceptibility gene Trio in cerebellar Purkinje cells leads to delayed motor impairments.zip by Jinxin Wang (1696837)

    Published 2025
    “…<p>Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by social interaction deficits, restricted interests and repetitive behaviors. …”
  13. 18693

    Model comparison experimental results. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  14. 18694

    DataSheet3_Deficiency of autism susceptibility gene Trio in cerebellar Purkinje cells leads to delayed motor impairments.zip by Jinxin Wang (1696837)

    Published 2025
    “…<p>Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by social interaction deficits, restricted interests and repetitive behaviors. …”
  15. 18695

    Slicing aided hyper inference algorithm. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  16. 18696

    Microbiome-host genetic association. by Tamizhini Loganathan (18538349)

    Published 2025
    “…Core microbiome and correlation analysis at the phylum and genus levels identified significant microbiota. Specifically, the abundance of genera such as <i>Pseudomonas</i> and <i>Akkermansia</i> decreased, while <i>Ruminococcus</i> and <i>Allistipes</i> increased, as determined by statistical and machine learning approaches. …”
  17. 18697

    Summary description of the samples. by Tamizhini Loganathan (18538349)

    Published 2025
    “…Core microbiome and correlation analysis at the phylum and genus levels identified significant microbiota. Specifically, the abundance of genera such as <i>Pseudomonas</i> and <i>Akkermansia</i> decreased, while <i>Ruminococcus</i> and <i>Allistipes</i> increased, as determined by statistical and machine learning approaches. …”
  18. 18698

    Improved YOLOv10 network structure. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  19. 18699

    Loss function variation curve. by Chunhua Yang (346871)

    Published 2025
    “…The experimental results demonstrate that when compared to YOLOv10, S-YOLOv10-ASI shows significant improvements across various metrics. Specifically, Bounding Box Regression Loss decreases by over 30% in the training set, while Classification Loss and Bounding Box Regression Loss drop by more than 60% in the validation set. …”
  20. 18700

    Type level landscape index changes in 1990-2020. by Chao Ma (207385)

    Published 2025
    “…The habitat quality shows a spatial distribution pattern of “high in the surrounding areas and low in the central areas”, and autocorrelation analysis shows that county-level units have significant spatial agglomeration effects. …”