Design of a Progressively Expandable Stent Using Finite Elements
Bibliographic record
Abstract
Currently, a minimally invasive surgery called stenting is extensively used to increase the lumen of partially obstructed arteries. Unfortunately, restenosis, a postoperative phenomenon in which the lumen of the artery is reduced due to a traumatism of the artery, is still a concern. The most popular solution that has been adopted by stent manufacturers comprises drug-eluting stents. This paper presents a new stent concept in which the treatment of restenosis is carried out from a completely different angle. Indeed, instead of traumatizing the artery, and then trying to control restenosis with drugs, the new stent minimizes the traumatism of the artery by expanding itself, not instantaneously, but progressively, and in a controlled manner. To achieve this, a nitinol stent over which a series of polymer rings are installed tries to reach a fully deployed configuration, but the polymer rings, which act as a retainer, become soft over time due to creeping. Thus, after the initial deployment in the artery, the stent continues its expansion autonomously over an extended period of time (a few weeks). It is believed that the artery has enough time to adapt to the expansion, leading to minimum traumatism. This paper presents the stent design.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".