Structural plane recognition effect. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Structural plane classification. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Mixup data expansion. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Marking example. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Description of results of SD-TOPSIS application (combination A) using selected moment characteristics. by Roman Vavrek (13200141)

Average TF VA for 3 pupil diameters (3, 4 and 5-mm) under paralyzed accommodation. by Shrilekha Vedhakrishnan (12256977)

TFVA data shown for all subjects and conditions under paralyzed accommodation with 5 mm pupil diameters. by Shrilekha Vedhakrishnan (12256977)

The N-terminal domain is sufficient for CMPK2 antiviral function. by Joanna B. Pawlak (5210639)

Table 5_Active ingredients isolated from Periplaneta americana L. inhibit the inflammation of the colonic mucosa and regulate the gut microbiota in DSS-induced ulcerative colitis i... by Yanhuan Wang (12037016)

Habitat suitability index (HSI) trend (seasonal and random components removed) time-series and Time of Emergence (ToE; vertical lines) for changes in HSI within CCE shelf-outer slo... by Ryan Gasbarro (6872717)

Drill image dataset for training part II. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

U²-Net network structure diagram [8]. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

RSU-7 structure diagram [8]. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Drill image dataset for training part I. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Change in foldability during evolution for subsets of chain size: Distribution of domain length for domains appearing a) 3.8-1.5 Gya and b) 1.5-0 Gya. by Cédric Debès (102067)

Cytokine co-expression of SARS-CoV-2 specific T cells differs between PASC and RC. by Katherine M. Littlefield (12647420)

The significant decrease in GLT-1 levels observed in the nucleus accumbens of rats that had consumed morphine for fifty-six days was completely reversed by the co-administration of... by María Elena Quintanilla (8068691)

Image_1_The Cds.71 on TMS5 May Act as a Mutation Hotspot to Originate a TGMS Trait in Indica Rice Cultivars.jpeg by Yanning Tan (3934751)

“…In T98S, the candidate gene TMS5 (LOC_Os02g12290.1) mutated at cds.71 with a transversion from cytosine (C) to adenine (A), as also observed in AnS and ZhS. …”

Table_1_The Cds.71 on TMS5 May Act as a Mutation Hotspot to Originate a TGMS Trait in Indica Rice Cultivars.doc by Yanning Tan (3934751)

“…In T98S, the candidate gene TMS5 (LOC_Os02g12290.1) mutated at cds.71 with a transversion from cytosine (C) to adenine (A), as also observed in AnS and ZhS. …”

Overexpression <i>TRIM37</i> promotes myelin repair and inhibits cell apoptosis by upregulating PEX5. by Lai Jiang (2401513)

“…<p><b>(a, b)</b> Western blot (n = 3) showed a significant increase in PEX5 protein levels in the OE-TRIM37 group compared to the LPC group. …”