Temporal Flow Evolution on a Pediatric Ventricular Assist Device
Bibliographic record
Abstract
The transplant line is long and slow for patients with cardiac diseases, especially children.The support of ventricular assist devices (VAD) may stabilize the patient until a suitable donor is found.VADs are auxiliary pumps that help the failing heart to pump the blood.However, the use of a VAD is associated with clinical complications due to blood trauma (hemolysis) or thrombus formation.The destruction of the blood cells is strongly correlated with the shear stress that is imposed in the flow through all the devices parts, while regions of very slow velocities (stagnation) may increase the probability of thrombus formation.One particularly difficulty lies in pediatric devices due to strong variations in sizes and flows to accommodate children of various ages.To allow future improvement in the PVAD, the present work aims to analyze the temporal flow evolution inside a pulsatile pediatric ventricular assistance device (PVAD) under development in our institution.The time resolved particle image velocimetry technique was used to observe the evolution of flow structures inside the device.In this study, three parallel planes were studied to visualize the three-dimensionality of the flow.In the experiments, the acquisition rate was 3250 Hz and pumping rate set at 70 bpm.The results show important asymmetries in the filling and ejection periods especially near the valves.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".