Dynamic Characterization of Parametric Structures and Perturbation Analysis of Blood Flow in the Cranial Arteries
Bibliographic record
Abstract
Stroke is considered the second leading cause of death globally.The primary risk factor for stroke-related diseases is high blood pressure, which occurs as a result of insufficient blood transport to the brain due to blockages or ruptures in the blood vessels.This study presents the explicit finite-difference method through discretization of the solution domain of the 1-D Navier-Stokes equations capable of predicting pressure and flow profiles by characterizing key parameters of pressure variations inherent in the human cranial arteries.Interestingly, the results obtained shows that, the part of the wave with higher pressure travels faster to the periphery than the part with lower pressure.The increase in diastolic and a null decrease in systolic pressure as seen in our simulations is as a result of a slower heart rate, since the heart is taking longer time to complete a beat.Our findings shows that a decrease in the radius of the cranial artery from (0.29 -0.275) will result in the increase in pressure within the range (115 -145).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".