Reconstruction of RpoS regulon under both control and heat shock conditions. by Joon Young Park (15256702)

“…When the binding intensity of the two sigma factors increased, the expression level tended to be up-regulated, whereas when the binding intensity decreased, the expression level tended to be down-regulated. …”

Data Sheet 1_Increased maternal exercise of moderate intensity improves pregnancy outcomes of gestational diabetes mellitus patients through maintaining the balance of the gut micr... by Mengyan Xu (1893223)

“…At the genus level, LEfSe analysis revealed that moderate-intensity exercise increased the levels of Faecalibacterium, Agathobacter, Roseburia, and Osillospira, but decreased the abundance of Bifidobacterium and Coprobacillus.…”

Screw location map. by Petr Boháč (20685499)

“…Supplementary plate fixation decreases IFM distances in the proximal area but increases sliding distances in the same region. …”

The applied forces and moments. by Petr Boháč (20685499)

“…Supplementary plate fixation decreases IFM distances in the proximal area but increases sliding distances in the same region. …”

The applied forces and moments for the muscles. by Petr Boháč (20685499)

“…Supplementary plate fixation decreases IFM distances in the proximal area but increases sliding distances in the same region. …”

Shrimp allergen extract (SAE) immunotherapy preventing the development of allergies. by Honey Dzikri Marhaeny (20480031)

Changes in volume, mass, and end-diastolic strain during experimental MR in dogs. by Johane H. Bracamonte (12883844)

Fig 5 - by Joon Young Park (15256702)

“…The binding intensity of RpoS upstream of <i>cyxAB</i> significantly increases in response to heat shock. (E) RpoD binding events upstream of TUs for NADH:quinone oxidoreductase and ATP synthase. …”

A proposed model on the impact of DHA and ARA supplementation on <i>L. vannamei</i> health. by Virak Visudtiphole (11574169)

Quantitative results on WEDU dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Counting results on DRPD dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Quantitative results on RFRB dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Main module structure. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Counting results on MTDC-UAV dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Quantitative results on DRPD dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Architecture of MAR-YOLOv9. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Quantitative results on MTDC-UAV dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Counting results on WEDU dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Example images from four plant datasets. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”

Counting results on RFRB dataset. by Dunlu Lu (19964225)

“…The hybrid connection strategy allows the model to flexibly utilize features from different levels. This solves the issues of increased training time and redundant weights caused by the detection neck and auxiliary branch structures in traditional YOLOv9, enabling MAR-YOLOv9 to maintain high performance while reducing the model’s computational complexity and improving detection speed, making it more suitable for real-time detection tasks. …”