Activities of the cavitation bubbles in the wake of a shock pressure pulse recorded by an optical fiber hydrophone
Bibliographic record
Abstract
The shock pulse used in an extracorporeal shock wave treatment (ESWT or ESWL) has a large negative pressure (< -5MPa) which can always produce acoustic cavitation. The resulting cavitation bubbles are known to play an important role in therapeutic effects, however, the bubble activities are not readily measurable yet. The present study considered a weird tail after the negative peak in the time history of pressure sensed by an optical fiber hydrophone which was usually abandoned in typical pressure field measurements. A shock pressure pulse in water causes change of mass density which modulates the optical refractive index. The change of the refractive index can be measured by the light reflection at the tip of the glass fiber submerged in water. The loss of water contact by cavitation bubbles at the fiber tip leads to an abnormal increase of high reflection which is clearly identified. This suggests that the weird tail of the hydrophone signal beyond the negative cycle of a shock pulse is closely related to the extent of the cavitation bubbles. This was experimentally validated in the shock wave field which was produced in water by a clinical ESWT system (ShineWave, HnT Medical, Republic of Korea) with an optical hydrophone (FOPH2000, RP Acoustics, Germany). Keywords: shock pressure pulse, ESWT, ESWL, cavitation, bubbles, optical fiber hydrophone
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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 | 0.000 |
| 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) | 0.001 | 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".