Evaluation of the properties of daughter bubbles generated by inertial cavitation of preformed microbubbles
Bibliographic record
Abstract
Inertial cavitation (IC) of the preformed microbubbles is being investigated for ultrasound imaging and therapeutic applications. However, microbubbles rupture during IC, creating smaller daughter bubbles (DBs), which may cause undesired bioeffects in the target region. Thus, it is important to determine the properties of DBs to achieve controllable cavitation activity for applications. In this study, we theoretically calculated the dissolution dynamics of sulfur hexafluoride bubbles. Then, we applied a 1-MHz single tone burst with different peak negative pressures (PNPs) and pulse lengths (PLs), and multiple 5-MHz tone bursts with fixed acoustic conditions to elicit IC of the preformed SonoVue microbubbles and scattering of DBs, respectively. After the IC and scattering signals were received by a 7.5-MHz transducer, time- and frequency-domain analysis was performed to obtain the IC dose and scattering intensity curve. The theoretical dissolution curves and measured scattering intensity curves were combined to determine the effect of the incident pulse parameters on the lifetime, mean radius and distribution range of DBs. Increased PNP reduced the lifetime and mean size of the DBs population and narrowed the size distribution. The proportion of small DBs (less than resonance size) increased from 36.83% to 85.98% with an increase in the PNP from 0.6 to 1.6 MPa. Moreover, increased PL caused a shift of the DB population to the smaller bubbles with shorter lifetime and narrower distribution. The proportion of small bubbles increased from 25.74% to 95.08% as the PL was increased from 5 to 100 µs. Finally, increased IC dose caused a smaller mean size, shorter lifetime and narrower distribution in the DB population. These results provide new insight into the relationship between the incident acoustic parameters and the properties of DBs, and a feasible strategy for achieving controllable cavitation activity in applications.
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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) | 0.000 | 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 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".