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Record W4399446531 · doi:10.1016/j.ohx.2024.e00540

A low-cost, portable device for the study of the malaria parasite’s growth inhibition via microwave exposure

2024· article· en· W4399446531 on OpenAlexfundno aff
Esteban Rua, Lorena Coronado, Carlos A. Donado Morcillo, Ricardo Correa, Lina Solís, Carmenza Spadafora, Alejandro Von Chong

Bibliographic record

VenueHardwareX · 2024
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsnot available
FundersCanadian Space AgencyUniversidad Tecnológica de PanamáNational Aeronautics and Space Administration
KeywordsMalariaInterface (matter)MicrowaveComputer scienceMatching (statistics)AmplifierEmbedded systemComputer hardwareTelecommunicationsMedicineImmunologyOperating systemPathology

Abstract

fetched live from OpenAlex

Recently, a novel method for the growth inhibition of malaria parasites using microwaves was proposed. However, the apparatuses used to demonstrate this method are high-cost and immovable, hindering the progression in this field of research, which is still in its early stages. This paper presents the redesign, construction, and validation of an equivalent system, converting it into a portable and low-cost system, capable of replacing the existing one. The proposed system is mainly composed of an RF generator (MAX2870), an RF amplifier (SKYWORKS 66292-11) and a graphical user interface. Likewise, the RF applicator proposed by the original study was redesigned, resulting in a five-fold improvement in return loss. The obtained results indicate that the proposed system achieves 90% parasite growth inhibition, matching the performance of its counterpart at less than 1% of its cost. These results represent a breakthrough for the creation of smaller, enhanced devices that open new possibilities for an alternative treatment to combat this devastating disease.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.013
GPT teacher head0.222
Teacher spread0.209 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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