Model comparison experimental results. by Chunhua Yang (346871)

“…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. …”

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

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

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

“…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. …”

Data Sheet 3_Genome-wide identification of GDPD gene family in foxtail millet (Setaria italica L.) and functional characterization of SiGDPD14 under low phosphorus stress.docx by Chaomin Meng (21496829)

“…Under low phosphorus stress, the expression levels of SiGDPD3 and SiGDPD14 significantly increased, while SiGDPD1, SiGDPD5, SiGDPD6, and SiGDPD11 showed significant decreases.To identify the function of SiGDPD14, an over-expressed transgenic Arabidopsis was generated. …”

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

“…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. …”

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

“…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. …”

Improved YOLOv10 network structure. by Chunhua Yang (346871)

“…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. …”

Image 2_Genome-wide identification of GDPD gene family in foxtail millet (Setaria italica L.) and functional characterization of SiGDPD14 under low phosphorus stress.png by Chaomin Meng (21496829)

“…Under low phosphorus stress, the expression levels of SiGDPD3 and SiGDPD14 significantly increased, while SiGDPD1, SiGDPD5, SiGDPD6, and SiGDPD11 showed significant decreases.To identify the function of SiGDPD14, an over-expressed transgenic Arabidopsis was generated. …”

Image 3_The global burden of hypertension and its epidemiological impacts on adolescents and young adults: projections to 2050.jpeg by Chaofeng Niu (17746406)

“…</p>Results<p>From 1990 to 2021, the absolute numbers of hypertension-related deaths, Disability-Adjusted Life Years (DALYs), and Years Lived with Disability (YLDs) increased significantly globally. The age-standardized mortality rate and DALY rate decreased to some extent, while the YLDs rate increased slightly. …”

Loss function variation curve. by Chunhua Yang (346871)

“…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. …”

Data Sheet 2_Pandan–vanilla rotation mitigates Fusarium wilt disease in vanilla: insights from rhizosphere microbial community shifts.xlsx by Shan Hong (1938337)

“…Soil pH was identified as a significant factor influencing microbial community assembly. …”

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

“…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. …”

DataSheet2_Deficiency of autism susceptibility gene Trio in cerebellar Purkinje cells leads to delayed motor impairments.zip by Jinxin Wang (1696837)

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

Location map of the study area. by Chao Ma (207385)

“…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. …”

Image 2_Exploring the antibacterial and anti-biofilm properties of Diacerein against methicillin-resistant Staphylococcus aureus.tif by Yingying Sun (568696)

“…Background<p>Methicillin-resistant Staphylococcus aureus (MRSA) poses a significant clinical challenge due to its multidrug resistance. …”

Different model detection results comparison. by Chunhua Yang (346871)

“…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. …”

Data source. by Chao Ma (207385)

“…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. …”

Research Technology Flow Chart. by Chao Ma (207385)

“…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. …”

Presentation1_Pressure-tolerant survival mechanism of Schizophyllum commune 20R-7-F01 isolated from deep sediments 2 kilometers below the seafloor.pdf by Mengshi Zhao (20157978)

“…In this study, we investigated Schizophyllum commune 20R-7-F01 isolated from coal-bearing sediments at a depth of 2 km below the seafloor. By assessing the cell viability, biomass, and cell wall thickness changes of strain 20-7-1 under different HHP conditions, we observed that, compared to 0.1 MPa, strain 20-7-1 exhibited slower growth rates and decreased cell viability at 15 MPa and 35 MPa, yet demonstrated significant pressure tolerance. …”

Inner-IoU. by Chunhua Yang (346871)

“…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. …”