Evaluation metrics on test data. by Ayesha Khalid (7843483)

“…These findings underscore the effectiveness of the ESM-2 model in accurately predicting <i>O-</i>GlcNAc sites within human proteins. Accurately predicting <i>O</i>-GlcNAc sites within human proteins can significantly advance glycoproteomic research by enhancing our understanding of protein function and disease mechanisms, aiding in developing targeted therapies, and facilitating biomarker discovery for improved diagnosis and treatment. …”

Cell2Spatial enables versatile applications across various analytical domains. by Huamei Li (8815955)

Flowchart of the entire pipeline. by Andreas Denger (12111159)

Investigating the spatial architecture of the mouse kidney. by Huamei Li (8815955)

Performance assessment of Cell2Spatial in real ST data from various tissue types. by Huamei Li (8815955)

Performance assessment of Cell2Spatial on real and simulated mouse brain spatial transcriptomics (ST) data. by Huamei Li (8815955)

Summary: Dipole-spread-function engineering for simultaneously measuring the 3D orientations and 3D positions of fluorescent molecules by Tingting Wu (21440889)

“…We demonstrate the pixOL algorithm to simultaneously optimize all pixels within a phase mask to produce an engineered Green’s tensor–the dipole extension of point-spread function engineering. …”

Exploring the spatial architecture of the human dorsolateral prefrontal cortex (DPLFC). by Huamei Li (8815955)

Application of Cell2Spatial to 10× Genomics Xenium mouse brain data. by Huamei Li (8815955)

Evaluation of spatial transcriptomics (ST) tools across various metrics and conditions. by Huamei Li (8815955)

DataSheet1_The evolution of flexibility and function in the Fc domains of IgM, IgY, and IgE.pdf by Rosaleen A. Calvert (10039787)

“…This permits additional flexibility within the Fc region, which has been exploited by nature to modulate antibody effector functions. …”

Can geodemographic clustering be fair? Incorporating social fairness in crisp and fuzzy approaches through a unified framework by Yue Lin (13107042)

“…SFGC also introduces a gradient descent-based algorithm to optimize this new cost function. In addition, SFGC can be directly adapted to crisp clustering, facilitating practical implementation and comparison of clustering algorithms.…”

An HSR corridor with m stations and n trains. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Structure of bi-level programming model. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Lanzhou-Xi’an HSR corridor. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Comparison of related studies with our work. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Unit impedance of each OD pair. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Subscripts and parameters used in TSSN. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Occupying rate of v-class seat in each train. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Schematic diagram of mutation operation. by Zhipeng Huang (1759759)

“…We propose a time-space-state three-dimensional network (TSSN) that integrates preferences for travel time, fares, and seat classes. Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”