Image6_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image3_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image4_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Table3_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.docx by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Table2_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.docx by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image5_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image1_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image2_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.jpeg by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Table1_Overexpression of TaPIP1A enhances drought and salt stress tolerance in Arabidopsis: cross-species conservation and molecular dynamics.docx by Jie Han (128758)

“…In TaPIP1A knockout wheat strains, there was a significant decrease in stress tolerance, whereas Arabidopsis plants overexpressing TaPIP1A exhibited marked improvements in survival under similar stress conditions. …”

Image 1_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…We propose a two-step deep learning approach that leverages the strengths of pre-trained object detection models to detect two-wheeler riders and specialized helmet classifiers to identify helmet wear status as well as detect number plates. …”

Image 6_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…We propose a two-step deep learning approach that leverages the strengths of pre-trained object detection models to detect two-wheeler riders and specialized helmet classifiers to identify helmet wear status as well as detect number plates. …”

Image 7_Computer-vision based automatic rider helmet violation detection and vehicle identification in Indian smart city scenarios using NVIDIA TAO toolkit and YOLOv8.jpg by Uttam U. Deshpande (21758837)

“…We propose a two-step deep learning approach that leverages the strengths of pre-trained object detection models to detect two-wheeler riders and specialized helmet classifiers to identify helmet wear status as well as detect number plates. …”

Data Sheet 1_LoCS-Net: Localizing convolutional spiking neural network for fast visual place recognition.pdf by Ugur Akcal (20633144)

“…Hardware-in-the-loop tests using Intel's neuromorphic USB form factor, Kapoho Bay, show that our on-chip spiking models for VPR trained via the ANN-to-SNN conversion strategy continue to outperform their SNN counterparts, despite a slight but noticeable decrease in performance when transitioning from off-chip to on-chip, while offering significant energy efficiency. …”

Data Sheet 1_The secreted host-cell protein clusterin interacts with PmpD and promotes Chlamydia trachomatis infection.pdf by Fabienne Kocher (20620811)

“…In infection experiments, depletion of sCLU from the culture medium leads to a significant decrease in Ctr infection. Thus, sCLU is the first host-cell interaction partner identified for a Ctr Pmp and the first case in which sCLU has been shown to be a vital component for the establishment of a bacterial infection.…”

Table 6_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.xlsx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”

Table 2_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.xlsx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”

Table 3_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.xlsx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”

Table 1_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.xlsx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”

Table 4_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.xlsx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”

Data Sheet 1_Quantitative proteomic analysis reveals potential serum diagnostic markers for colorectal adenoma.docx by Chengli Yu (1445185)

“…</p>Results<p>In two independent cohorts, we identified two candidate biomarkers, apolipoprotein A4 (APOA4) and filamin A (FLNA), through a multi-step selection process involving ANOVA p-value screening, sparse partial least squares discriminant analysis (sPLS-DA), and LASSO regression analysis. …”