Comparison between different PSO algorithms on function 1–3. by Lai Xu (1828831)

“…<p>Comparison between different PSO algorithms on function 1–3.</p>…”

Similarity between the allegiance matrices of the multiplex SC-FC graph, the FC graph alone, and the SC graph alone, as a function of the topological scale for the group. by Arian Ashourvan (6685232)

Similarity between the hierarchical community structure of structural and functional brain graphs. by Arian Ashourvan (6685232)

Local topological scales of hierarchical community organization in structural and functional brain graphs. by Arian Ashourvan (6685232)

Showing the Quantum Mechanics-based Density Functional Theory optimisation of 3-1-BCMIYPPA where different energy levels are shown in different colours. by Mohammed Ali Alshehri (11707406)

Comparison between different PSO algorithms on function 4–6. by Lai Xu (1828831)

Comparison between different PSO algorithms on function 7–8. by Lai Xu (1828831)

Fold Change (FC) in protein levels among non-survivors compared to survivors in 40 CERES participants. by Yue Ren (1311615)

Subjects:

Algorithm membership function. by Mohamed Raef Smaoui (9865830)

“…<p>(Top) Input Membership Function. The algorithm classifies glucose input into 4 sets: low, medium, high, and ex_high. …”

Significantly dysregulated proteins (|log2FC | ≤  0.5, adj. p-value ≤  0.05) in SCA1 (805 proteins). by Aimilia-Christina Vagiona (17584758)

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

“…Introduction<p>Antibody Fc regions harbour the binding sites for receptors that mediate effector functions following antigen engagement by the Fab regions. …”

RMSE values of different algorithms for different bands in the "Kherson" region. by YueSheng Jiang (19267984)

RMSE values of different algorithms for different bands in the "PY" region. by YueSheng Jiang (19267984)

Performance of the Algorithm 1. by Bogumił Kamiński (7827794)

Data of PV, WT, FC, and utilized coefficients. by Obaid Aldosari (19797428)

“…Analyzing three case studies depending on the objective function—Case 1: execute EM to minimize total operation cost and maximize the profits of BSS, Case 2: execute EM to minimize total emission from the μG, and Case 3: execute EM to minimize total operation cost, maximize the profits of BSS, and minimize total emissions from the μG. …”

Mutations of the gene expression fold change (FC) over wildtype. by Fangzhou Shen (5140994)

Changes in the relative abundances of signaling functions across initial GA-LR pairs. by Erick Armingol (5125595)

“…Changes were computed from the fold change (FC) between the relative abundance in each of the 100 runs of the genetic algorithm (GA) with respect to the corresponding relative abundance in the complete list of LR pairs (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010715#pcbi.1010715.s002" target="_blank">S1 Table</a>), and shown as the log10(FC+1) transformation (x-axis). …”

Algorithm 1. by Muhammad Zubair Rehman (11243478)

Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>14−<i>f</i>23.…”

Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13. by Ying Li (38224)

“…<p>Convergence curves of the IMGO algorithm and comparison algorithms on functions <i>f</i>8−<i>f</i>13.…”