Summary of miRNAs sequencing data quality. by Zhaowen Tan (12283502)

“…</p><p>Results</p><p>1) Hemodynamic tests revealed that the blood pressure of SHRs in the BFRT decreased significantly and that the blood pressure level of SHRs in the BFRT decreased more significantly than that of the simple resistance training groups did (P < 0.05). 2) Cardiac function tests revealed that the EF, FS, and MV E/A of SHRs in the BFRT significantly increased, whereas the HR, IVSd, IVSs, LVIDd, LIVDs, LVPWd, LVPWs and LV mass significantly decreased (P < 0.05). 3) Transcriptome sequencing revealed 9 differentially expressed miRNAs in the BFRT group compared with the SHR-SED group (2 miRNAs were significantly upregulated, and 7 miRNAs were significantly downregulated), with P < 0.05 and |log2FoldChange| ≥ 1 used as the criteria for differential significance. …”

The miRNA target genes. by Zhaowen Tan (12283502)

“…</p><p>Results</p><p>1) Hemodynamic tests revealed that the blood pressure of SHRs in the BFRT decreased significantly and that the blood pressure level of SHRs in the BFRT decreased more significantly than that of the simple resistance training groups did (P < 0.05). 2) Cardiac function tests revealed that the EF, FS, and MV E/A of SHRs in the BFRT significantly increased, whereas the HR, IVSd, IVSs, LVIDd, LIVDs, LVPWd, LVPWs and LV mass significantly decreased (P < 0.05). 3) Transcriptome sequencing revealed 9 differentially expressed miRNAs in the BFRT group compared with the SHR-SED group (2 miRNAs were significantly upregulated, and 7 miRNAs were significantly downregulated), with P < 0.05 and |log2FoldChange| ≥ 1 used as the criteria for differential significance. …”

Differential miRNA target gene pathway enrichment bubble map. by Zhaowen Tan (12283502)

A. Representative data of NB4 cells (treated with LPS and RSV) ETOsis percentage by Flow cytometry method. NB4 cells are stimulated with LPS (1). NB4 cells are treated with 5 µ M R... by Mahshid Vafajoo (21144147)

(A) Hierarchical clustering results of differential proteins in the Model.vs.WKY; (B) Differential protein enrichment bar chart in the Model.vs.WKY; (C) Significantly enriched path... by Xiao Zhang (152326)

Path diagram of the 2-factor CFA analysis. by Vincenza Tarantino (182506)

“…As expected, a significant correlation between the S-Hab-Q and the AQ score was found. …”

Summary of previous work. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Comparison of MAP@0.5 results from experiments. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

YOLO11. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Structure of the SCI-YOLO11 network. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Comparative experimental results. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

SCI-YOLO11. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Dataset for insulator defect detection. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

YOLOV8. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Faster-RCNN. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Results of ablation experiments. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Structure diagram of SPDConv. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Wise-IOU regression diagram. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Visualization of detection results. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”