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Record W4285265785 · doi:10.1051/e3sconf/202235403002

An Assessment of the Use of Static Magnetic Field for Sodium Fluoride Defluoridation and Removal of Escherichia Coli and Rotavirus Pathogens from Water

2022· article· en· W4285265785 on OpenAlexaff
Mary T. Simiyu, Francis Nyongesa, Bernard O. Aduda, Zephaniah Birech, Illic Nikolina

Bibliographic record

VenueE3S Web of Conferences · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMagnetic and Electromagnetic Effects
Canadian institutionsUniversity of Toronto
FundersFonds National de la Recherche LuxembourgNational Research Fund, Kenya
KeywordsPortable water purificationFiltration (mathematics)Ultrafiltration (renal)Reverse osmosisNanofiltrationChemistryWater treatmentDesalinationChromatographyFluorideForward osmosisMembranePurified waterEnvironmental engineeringPulp and paper industryEnvironmental scienceInorganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

The use of chemicals such as chlorine in water purification leaves harmful biproducts in the water while filtration techniques such as reverse osmosis, ultrafiltration, nanofiltration, and forward filtration are costly and require external energy for their operation. Ceramic water filters that would have addressed these issues are brittle and incapable of filtering viruses. In this work, we report on the efficiency of water purification using a 0.8 T static magnetic field from permanent magnets in defluoridation of sodium fluoride and purification of Escherichia coli , and Rotavirus. The contaminated water was circulated at varying velocities of 0.1 ml/s to 2.0 ml/s at an ambient temperature of 16.0 °C to 40.0 °C for 0.5 hours to 9.0 hours. It was found that when ionized water was circulated under the static magnetic field for nine hours, its pH was lowered by 9.7% and the velocity of water in circulation did not affect the purification efficiency. The static magnetic field equally lowered the replication of Escherichia coli and Rotavirus by 9.8% and 7.1% respectively. Furthermore, 14.1% of defluoridation of water was also achieved. Thus, a 0.8 T static magnetic field was not able to purify water to recommended levels.

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 score0.030
Threshold uncertainty score0.249

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 head0.015
GPT teacher head0.265
Teacher spread0.250 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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