Candidate genes were analyzed by three machine learning algorithms: LASSO regression, support vector machine recursive feature elimination (SVM-RFE), and Boruta. (A) SVM-RFE analys... by Xiaoyu Shen (4715430)

Consensus clustering base on expression of cuproptosis genes. by Hongmin Luo (2142307)

Development and characterization of a cell-type-specific gene expression reference panel from single-nucleus RNA sequencing (snRNAseq). by Brian Gural (21781982)

Data Sheet 4_Mitophagy-associated biomarkers and macrophage involvement in pulmonary arterial hypertension: identification and functional implications.zip by Xiaoyu Zhang (62901)

Data Sheet 3_Mitophagy-associated biomarkers and macrophage involvement in pulmonary arterial hypertension: identification and functional implications.zip by Xiaoyu Zhang (62901)

Data Sheet 2_Mitophagy-associated biomarkers and macrophage involvement in pulmonary arterial hypertension: identification and functional implications.zip by Xiaoyu Zhang (62901)

List of organoids lines used in the research. by Anna Demchenko (18449439)

“…The model demonstrated a high level of accuracy, as evidenced by an intersection-over-union metric (IoU) of 0.8856, F1-score = 0.937 and an accuracy of 0.9953. Applied to forskolin-induced swelling assays of lung organoids, the algorithm successfully quantified functional differences in Cystic Fibrosis Transmembrane conductance Regulator (CFTR)-channel activity between healthy donor and cystic fibrosis patient-derived organoids, without fluorescent dyes. …”

Redundancy optimization and reliability evaluation of (<i>k</i>₁, <i>k</i>₂)-out-of-<i>n</i>: G retrial system with redundant dependency and working vacation by Qi Shao (2394193)

“…Using Markov process theory, the transition rate matrix and steady-state equations of the system state are given, and the steady-state availability of the system is obtained. The reliability function and mean time to first failure (MTTFF) of the system are derived, and the Runge-Kutta algorithm for calculating the reliability function of the system is given. …”

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.…”

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Learning alters pirouette decision and behavioral noise. by Kevin S. Chen (9201767)

Model-based decoding of learning. by Kevin S. Chen (9201767)

(A) The PPI network was mapped using the STRING visualization tool. by Zhikai Su (21144119)

DA OPRESSÃO ALGORÍTMICA À ÉTICAEMERGENTE: O COLAPSO DAS WMDS EA FUNÇÃO Ƹ* COMO HORIZONTE DANORMATIVIDADE COMPUTÁVEL by LEONARDO COSTA (21212537)

“…The results pointtoward a new horizon for computable ethics: not one that replicateshuman morality, but one that structurally refuses harm as a function ofinferential instability. …”

Real time spike sorting with latencies in the range of synaptic transmission. by Tjitse van der Molen (20391106)

Spike cluster splitting based on amplitude and interelectrode interval distribution. by Tjitse van der Molen (20391106)

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. …”