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Record W2738225660

USING THE RESERVOIR WAVE APPROACH TO STUDY THE HORIZON EFFECT

2016· article· en· W2738225660 on OpenAlexaffvenue
Anh T.P. Nguyen, Lindsay M. Burrowes, Carol A. Gibbons Kroeker, Nigel G. Shrive, John V. Tyberg

Bibliographic record

VenueJournal of undergraduate research in Alberta · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsReflection (computer programming)Reflector (photography)MechanicsFlow (mathematics)Frequency domainPhysicsGeologyElectrical impedanceWave impedanceMathematicsOpticsMathematical analysisComputer science
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION Differing theories and models have been explored in the field of arterial hemodynamics in an effort to better understand how the blood flows in the body. The existence of discrete reflection sites remains a source of disagreement. As a wave proceeds along an artery, any local change in impedance will result in partial reflection. Thus, because of the great complexity of the arterial system, it has been suggested that no distinct reflector sites should exist. On the other hand, there is recent experimental evidence using the reservoir-wave approach (RWA) that implies discrete positive and negative reflection sites. The pattern of wave propagation and reflection is plausible, as are the modifications produced by pharmacologic interventions [1]. The classical, frequency-domain, “impedance analysis” approach uses Fourier analysis to break down pressure and flow waveforms into summations of sinusoids, resulting in an impedance spectrum [2]. The RWA is a novel alternative, positing that measured pressures and flows are the instantaneous sums of “excess” (wave-related) and reservoir (volume-related) components [2]. The “Horizon Effect” (HE) [3] implies that a reflector site can never be reached no matter how far into the periphery one measures (Figure 1). As such, it supports the idea that there are no distinct reflector sites. Measuring peripheral pressure and flow and using the RWA, the purpose of this study was to evaluate the HE and the question of fixed reflector sites. METHODS Eight anesthetized pigs were catheterized and pressure and flow were measured simultaneously at 4 locations: the aortic root and the brachial, carotid and renal arteries. Pharmacologic interventions were used to manipulate propagation and reflection patterns. MatLab (The MathWorks Inc., Natick, MA) was used to calculate the reservoir pressure, the local wave speed and to carry out wave intensity analysis (WIA) to obtain the forwards and backwards components of pressure. RESULTS Analysis has been completed on 4 of the 8 animals studied. Each showed minimal backward wave activity at the aortic root and in the carotid artery. However, in the brachial and renal arteries, no backward waves could be detected. DISCUSSION AND CONCLUSIONS Backward waves were scarcely detected in the periphery using either the RWA or classical analysis. This may suggest that the pig model was inappropriate to study the HE. Porcine anatomy does not allow measurement at remote peripheral sites and reflection sites cannot be studied if no reflections are to be found. Further analysis of the data is needed before more definitive conclusions can be made.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.143
GPT teacher head0.423
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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