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Record W2526377684 · doi:10.11159/icepr16.108

Removal of Mixed Heavy Metals and Pahs by Immobilized Selenastrum Capricornutum

2016· article· en· W2526377684 on OpenAlexvenueno aff
N.F.Y. Tam, Ping Wang, Dan Deng, Yuk-Shan Wong

Bibliographic record

VenueProceedings of the World Congress on New Technologies · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMineralogy and Gemology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSelenastrumHeavy metalsEnvironmental chemistryEnvironmental scienceChemistryToxicityOrganic chemistry

Abstract

fetched live from OpenAlex

Due to rapid industrialization and urbanization, toxic pollutants are found in industrial discharges causing serious environmental problems. Polycyclic aromatic hydrocarbons (PAHs) from all combustion and industrial activities are released into environments and biomagnified through food chains resulting hazards to humans and wildlife due to their persistence and toxicity. PAHs from industries such as hydrocarbon processing, iron/steel manufacturing, electronic manufacturing, dye manufacturing, electroplating, smelting, etc. are often co-contaminated with high levels of toxic heavy metals (HMs), particularly, cadmium (Cd), copper (Cu), zinc (Zn) and nickel (Ni). These pollutants must be removed prior to discharge. However, the removal of single pollutant could be different from that that under co-contamination with other pollutants, as interactions could occur between pollutants. Microalgae have been reported to have the ability to remove and degrade organic and inorganic pollutants in wastewater. Nevertheless, previous research mainly reported the removal of single pollutant with little consideration on the wastewater containing mixed pollutants. One of the major operation problems encountered in microalgal-wastewater treatment is the difficulty in separating the biomass from the treated effluent, due to the small particle size and low strength and density of the microalgal cell. Such harvesting problem in wastewater could be overcome by the immobilization of microalgal cells within a suitable matrix. However, the removal efficiency of immobilized cells may not be the same as that by the free cells. The present study aimed to investigate the simultaneous removal of mixed heavy metals (Cu, Zn, Ni and Cd) and polycyclic aromatic hydrocarbons (PAHs) of different molecular weights (fluorene, phenanthrene, fluoranthene, pyrene and benzo[a]pyrene) by alginate-immobilized beads of a freshwater commercial green microalgal species, Selenastrum capricornutum, and the feasibility of using immobilized microalgal beads for wastewater treatment.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.208
Teacher spread0.197 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

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