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Record W2584738774 · doi:10.1364/ol.42.000655

Photoacoustic resonance by spatial filtering of focused ultrasound transducers

2017· article· en· W2584738774 on OpenAlexafffund
Dongyel Kang, Bahman Lashkari, Andreas Mandelis

Bibliographic record

VenueOptics Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Research Foundation of KoreaMinistry of EducationCalifornia HIV/AIDS Research Program
KeywordsResonance (particle physics)DetectorOpticsTransducerAttenuation coefficientAperture (computer memory)PhysicsWavelengthPhotoacoustic spectroscopyAbsorption (acoustics)UltrasoundMaterials sciencePhotoacoustic effectUltrasonic sensorPhotoacoustic imaging in biomedicineAcousticsAtomic physics

Abstract

fetched live from OpenAlex

The effect of a spherically focused ultrasound (US) transducer (TD) on photoacoustic (PA) measurements is analytically investigated using the concept of a virtual point detector. The derived analytical results indicate that the limited numerical aperture (NA) of the PA detector takes on the role of spatial filtering of the induced PA waves, which leads to the occurrence of a peak frequency in the PA spectrum. The mathematical description of this phenomenon is similar to the result of resonance peaks of light propagation in dielectrics. This PA resonance peak depends on the NA of the US TD and the absorption coefficient of the PA source. Experimentally measured PA spectra from an ink solution using a frequency-domain PA system verify the PA resonance effect. Finally, we discuss the possibility that previously reported PA resonances interpreted as PA source viscosity might be actually caused by the US TD's spatial filtering.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.200
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2017
Admission routes2
Has abstractyes

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