Study of the effect of stenosis severity and non-Newtonian viscosity on multidirectional wall shear stress and flow disturbances in the carotid artery using particle image velocimetry
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 development of atherosclerosis at the carotid bifurcation is impacted by local variations in wall shear stress (WSS) magnitude and direction, as well as flow complexity within the vessel. In this study, stereoscopic particle image velocimetry (PIV) was used to investigate multidirectional WSS and disturbed flow for idealized models of the carotid bifurcation with varying eccentric stenosis of the internal carotid artery (ICA) and both Newtonian (N-fluid) and non-Newtonian (nN-fluid) blood analogues. Turbulence intensity (TI) was reduced with the nN-fluid compared to N-fluid for mild to moderate stenosis, and comparable for more severely stenosed (70%) models. Differences in maximum TI due to viscosity model ranged from 0.02 m/s to 0.06 m/s compared to much larger differences due to geometry of up to 0.29 m/s between mild and severe stenosis. The level of time-averaged WSS (TAWSS) increased with stenosis severity from 5 Pa to 32 Pa, and nN-fluid led to higher WSS on average than N-fluid counterparts. Regions of elevated oscillatory shear index (OSI) demarcated recirculation regions, and mean OSI in the ICA branch was reduced for nN-fluid models by 9-19% compared to N-fluid. Transverse WSS (transWSS) increased with WSS magnitude and again was higher in nN-fluid models. Surface area exposure to shear metrics indicated that a Newtonian viscosity assumption predicted larger regions of low and oscillatory WSS, while predicting reduced regions of high transWSS, in comparison to the more physiological shear thinning fluid.
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 | 0.000 |
| 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