A) Probability density of glucuronate-UDP as a function of three collective variables (CVs): the distance between the C6 atom of the sugar and the atom of Lys307, defined as <i>d</... by Davide Luciano (22822210)

Enhanced USV path planning through integrated Bi-RRT and DWA algorithms considering environmental factors by Yanghua Zhou (20449441)

“…Furthermore, the evaluation function of the DWA algorithm undergoes enhancements, incorporating elements from heuristic functions within the A* algorithm and radar-based assessment of search range. …”

Decoding results. by Sam Hall-McMaster (10343795)

The GA iteration result. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

GA crossover and mutation process. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The framework for the proposed model and GA-FNN. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The structure for the FNN. by Jiaqing Huang (5018492)

“…This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

Behavioral results. by Sam Hall-McMaster (10343795)

Identification of hub DE-SRGs. by Xihao Shen (20347942)

Spatial patterns of the CAPs estimated from both splits are reproducible and strongly correlated with at least one of the basis CAPs. by Kangjoo Lee (11648345)

Alphaviruses nsP4 protein alignment. by Marie-France Martin (12118879)

Significantly enriched Gene Ontology (GO) terms among the 512 genes showing significant results in the all ancestry TWAS. Enrichment analyses were conducted using the multi-query i... by Jenna C. Carlson (3950024)

Schematic diagram of the G4Hunter scanning principle. by Rongxin Zhang (1618159)

VEP annotation of the aSNPs listed in S1 Table. by Rongxin Zhang (1618159)

“…<div><p>G-quadruplexes (G4s) are nucleic acid secondary structures with important regulatory functions. Single-nucleotide variants (SNVs), one of the most common forms of genetic variation, can potentially impact the formation of G4 structures if they occur within G4 regions. …”

G4SNVHunter workflow for identifying variants that affect G4 formation. by Rongxin Zhang (1618159)

“…Subsequently, the impact of the variants on the formation potential of the identified G4s will be assessed based on the G4Hunter algorithm (Middle panel). Finally, candidate variants can be filtered and visualized using functions provided by G4SNVHunter to screen out those that can potentially disrupt the formation of G4 structures (Right panel). …”

S1 Dataset - by Ruochen Zhang (3434996)

“…The optimization results are further discussed to find specific paths for optimizing different objective functions. In general, adding edges within the same community is helpful for promoting ACC, while adding edges between different communities is beneficial for reducing APL. …”

Statistical tests of ACC on the random network. by Ruochen Zhang (3434996)

“…The optimization results are further discussed to find specific paths for optimizing different objective functions. In general, adding edges within the same community is helpful for promoting ACC, while adding edges between different communities is beneficial for reducing APL. …”

Parameters in the experiment. by Ruochen Zhang (3434996)

“…The optimization results are further discussed to find specific paths for optimizing different objective functions. In general, adding edges within the same community is helpful for promoting ACC, while adding edges between different communities is beneficial for reducing APL. …”

Statistical tests of APL on the random network. by Ruochen Zhang (3434996)

“…The optimization results are further discussed to find specific paths for optimizing different objective functions. In general, adding edges within the same community is helpful for promoting ACC, while adding edges between different communities is beneficial for reducing APL. …”

Statistical tests of ACC on the regular network. by Ruochen Zhang (3434996)

“…The optimization results are further discussed to find specific paths for optimizing different objective functions. In general, adding edges within the same community is helpful for promoting ACC, while adding edges between different communities is beneficial for reducing APL. …”