Structural Model for Viscoelastic Properties of Pericardial Bioprosthetic Valves
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The benefit of bioprosthetic aortic valve over mechanical valve replacements is the release of thromboembolism and digression of long-term anticoagulation treatment. The function of bioprostheses and their efficiency is known to depend on the mechanical properties of the leaflet tissue. So it is necessary to select a suitable tissue for the bioprosthesis. The purpose of the present study is to clarify the viscoelastic behavior of bovine, equine, and porcine pericardium. In this study, pericardiums were compared mechanically from the viscoelastic aspect. After fixation of the tissues in glutaraldehyde, first uniaxial tests with different extension rates in the fiber direction were performed. Then, the stress relaxation tests in the fiber direction were done on these pericardial tissues by exerting 20, 30,40, and 50% strains. After evaluation of viscoelastic linearity, the Prony series, quasilinear viscoelastic (QLV) and modified superposition theory were applied to the stress relaxation data. Finally, the parameters of these constitutive models were extracted for each pericardium tissue. All three tissues exhibited a decrease in relaxation rate with elevating strain, indicating the nonlinear viscoelastic behavior of these tissues. The three-term Prony model was selected for describing the linear viscoelasticity. Among different models, the QLV model was best able to capture the relaxation behavior of the pericardium tissues. More stiffness of porcine pericardium was observed in comparison to the two other pericardium tissues. The relaxation percentage of porcine pericardium was less than the two others. It can be concluded that porcine pericardium behaves more as an elastic and less like a viscous tissue in comparison to the bovine and equine pericardium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it