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Record W2167144390 · doi:10.1243/09544119jeim493

Design and simulation of a poly(vinyl alcohol)—bacterial cellulose nanocomposite mechanical aortic heart valve prosthesis

2009· article· en· W2167144390 on OpenAlexafffund
Hadi Mohammadi, Derek R. Boughner, Leonardo E. Millon, Wan Khairunizam

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine · 2009
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsVinyl alcoholNanocompositeMaterials scienceHyperelastic materialHeart valveAortic valveBiomaterialComposite materialCelluloseBacterial celluloseFinite element methodBiomedical engineeringCastingPolymerStructural engineeringChemical engineeringSurgeryNanotechnologyMedicineEngineering

Abstract

fetched live from OpenAlex

In this study, a polymeric aortic heart valve made of poly(vinyl alcohol) (PVA)-bacterial cellulose (BC) nanocomposite is simulated and designed using a hyperelastic non-linear anisotropic material model. A novel nanocomposite biomaterial combination of 15 wt % PVA and 0.5 wt % BC is developed in this study. The mechanical properties of the synthesized PVA-BC are similar to those of the porcine heart valve in both the principal directions. To design the geometry of the leaflets an advance surfacing technique is employed. A Galerkin-based non-linear finite element method is applied to analyse the mechanical behaviour of the leaflet in the closing and opening phases under physiological conditions. The model used in this study can be implemented in mechanical models for any soft tissues such as articular cartilage, tendon, and ligament.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.253
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations73
Published2009
Admission routes2
Has abstractyes

Explore more

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