DataSheet1_The evolution of flexibility and function in the Fc domains of IgM, IgY, and IgE.pdf حسب 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. …"

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. حسب María Victoria Waks-Serra (21578611)

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

The image of the Aekley function. حسب Zhengyu Xu (8550660)

Evolution of the rescaled hydraulic diameter () and complexity () in both simulations and seal tomograms as a function of simulation timestep and relative age (). حسب Jonathan E Kings (20818367)

The ALO algorithm optimization flowchart. حسب Wenjing Wang (181404)

"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"

The IALO algorithm solution flowchart. حسب Wenjing Wang (181404)

"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"

The impact of extrinsic noise sources on the measured SNR is plotted for both CW and TG against varying optical filter magnitudes. حسب Nicholas H. Vitale (20469289)

Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional حسب Ryan Stocks (16867476)

"…Kohn–Sham density functional theory (KS-DFT) has become a cornerstone for studying the electronic structure of molecules and materials. …"

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

The pseudocode for the NAFPSO algorithm. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

PSO algorithm flowchart. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

The traffic flow distribution diagram when traffic lights in both entrance and exit of the short-distance road section are red. حسب Yulin Tian (1457986)

The traffic flow distribution diagram when traffic lights in both entrance and exit of the short-distance road section are green. حسب Yulin Tian (1457986)

Comparison of different algorithms. حسب Dawei Wang (471687)

"…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …"

The benchmark functions. حسب Shuhui Yu (1535500)

Distributions of optimized coupling parameters and median FC strengths for males and females. حسب Kevin J. Wischnewski (21354521)

Study proposed algorithm. حسب Ainhoa Pérez-Guerrero (21377457)

"…The index of microvascular resistance (IMR) is a specific physiological parameter used to assess microvascular function. Invasive coronary assessment has been shown to be both feasible and safe. …"

Gillespie algorithm simulation parameters. حسب Nicholas H. Vitale (20469289)

"…Both the ensemble and stochastic models presented in this work have been verified using Monte Carlo molecular dynamic simulations that utilize the Gillespie algorithm. …"

Scheduling time of five algorithms. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"