Action potential of sample points in model 1. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Action potential of sample points in model 2. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Action potential of sample points in model 0. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Pareto optimal front result of MOCOA. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Confusion matrix. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Performance validation on the MIT-BIH database. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Performance comparison with other papers. by Hang Zhao (143592)

“…A finite element model (FEM) of the human heart, grounded in the Hodgkin-Huxley (HH) model was established to simulate cardiac electrophysiology, and ECG signals from 200 representative points were acquired. …”

Octree spatial visualization. by Gaia Marangon (22582137)

“…<div><p>This study presents a robust numerical framework for modeling bone tissue mechanics, integrating an orthotropic visco-plasto-damage model with high-resolution bone geometries derived from computed tomography (CT) scans. …”

Reduced yield-deformation parameters. by Gaia Marangon (22582137)

“…<div><p>This study presents a robust numerical framework for modeling bone tissue mechanics, integrating an orthotropic visco-plasto-damage model with high-resolution bone geometries derived from computed tomography (CT) scans. …”

Table 1_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Tensile (n = 113) and compressive (n = 137) tests were performed to obtain experimental data. An iFEA model with a Mooney–Rivlin hyperelastic formulation was developed to estimate the constitutive parameters of the meniscus through optimization algorithms.…”

Table 2_In Vitro biomechanical study of meniscal properties in patients with severe knee osteoarthritis.xlsx by Yuqi Liu (501183)

“…Tensile (n = 113) and compressive (n = 137) tests were performed to obtain experimental data. An iFEA model with a Mooney–Rivlin hyperelastic formulation was developed to estimate the constitutive parameters of the meniscus through optimization algorithms.…”

Supporting data for "Fracture and Non-linear Response of Biopolymer Network with Dynamic Cross-linkers" by Bingxian Tang (9151802)

“…This research aims to bridge these knowledge gaps by developing and employing a sophisticated computational model that accurately accounts for large deformations, thermal fluctuations, and forced crosslink breaking. …”

Yellow River Basin Industrial Base Spatio-temporal Monitoring and Impact Assessment Dataset by Libing Wang (21723566)

“…The dataset aggregates data elements and core algorithm codes that underpin the key research stages of the paper, with a focus on demonstrating and reproducing the innovative methodologies employed, rather than directly sharing sensitive raw data or precise measurement values.…”

Table 1_Reducing misdiagnosis in AI-driven medical diagnostics: a multidimensional framework for technical, ethical, and policy solutions.docx by Yue Li (102191)

Code repository by Dimitrios Iason Papadopoulos (21556811)

“…<br></pre><pre>This study investigates the integration of Structural Health Monitoring (SHM) systems, employing active piezoelectric sensors, with Machine Learning (ML) algorithms to develop robust, AI-driven diagnostic tools for composite structures. …”

Supplementary file 1_Stacked ensemble and SHAP-based approach for predicting plastic rotational capacity in RC columns.docx by Andrei-Odey Kadhim (22449631)

“…Finally, a stacking ensemble model was developed to integrate the strengths of the individual regressors. …”