Interaction of electromagnetic waves with biological tissue
Bibliographic record
Abstract
The interaction of electromagnetic waves with biological tissue is investigated. Two problems in particular are studied. The first is three-dimensional scattering from biological tissue taking into consideration its dispersive nature. The other problem that is investigated is the thre -dimensional reconstruction of the dielectric properties of a body from the scattered field data resulting from interrogation with electromagnetic waves. The symmetric condensed node transmission line matrix method (SCN TLM) is used to study three-dimensional scattering from biological tissue. To simulate the dispersive nature of biological tissue, a second order Debye equation approximation of the permittivity in the frequency domain is used in a modified TLM technique. In this technique, the scattering matrix is independent of the dielectric properties of the medium, which are accounted for via lumped equivalent networks or sources connected to the nodes. These equivalent sources are calculated at each time step and includedin the scattering procedure of the TLM. To check the validity and accuracy of the modified TLM technique for dispersive homogeneous and nonhomogeneous dielectric bodies, some of the results of the numerical simulations are compared to those obtained analytically. Assuming a nondispersive nature of biological tissue, the nondispersive or stub-loaded SCN TLM method is used to obtain the near field data and hence the specific absorption rate (SAR) distribution. The results of both cases are compared. The modified TLM technique is then applied to a nonhomogeneous and geometrically complex dispersive dielectric body, which is the human head. To estimate the complex permittivities of three-dimensional inhomogeneous dielectric bodies, the unrelated illumination method is used. This method, which has been tested before with two-dimensional bodies, is extended to handle three-dimensional inhomogeneous dielectric bodies. The method utilizes the method of moments (MoM) to discretize the nonlinear integral equation, which relates the scattered field data and the complex permittivity. Yet, it differs from the other reconstruction techniques in that the way of acquiring information helps overcoming the ill-posedness nature of the problem. This is maintained by the proper arrangement of the polarization and the direction of the incident electric fields aiming to illuminate the body with a group of unrelated incident fields. Numerical simulations are carried out to assess the method and to test its robustness in the presence of measured data uncertainties.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".