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Record W2149502867 · doi:10.1139/s06-033

Simple physical treatment for the reuse of wastewater from textile industry in the Middle East

2007· article· en· W2149502867 on OpenAlexvenueno aff
Hassan A. Arafat

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2007
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsnot available
FundersAn-Najah National University
KeywordsWastewaterChemical oxygen demandSedimentationFerricPulp and paper industryLimeFlocculationSewage treatmentSulfateAdsorptionActivated carbonWaste managementFerrousCoagulationPowdered activated carbon treatmentChemistryEnvironmental scienceEnvironmental engineeringMaterials scienceMetallurgyInorganic chemistryEngineeringGeologyOrganic chemistrySediment

Abstract

fetched live from OpenAlex

In this work, different treatment methods for wastewater from textile washing operations in the Palestinian territories were studied. The goal of the treatment process was to enable the textile industry to reuse the wastewater in textile washing through simple, efficient, and cost-effective methodologies. Actual textile wastewater samples from local textile factories were used and were found to be highly polluted. The study focused on three main processes; sedimentation, coagulation, and adsorption. While sedimentation was found to reduce the total suspended solids (TSS) of the wastewater, coagulation had the additional advantages of lowering the chemical oxygen demand (COD) and achieving higher filtration rates. Four coagulants were tested, ferric chloride, ferrous sulfate plus lime, aluminum sulfate, and aluminum sulfate plus lime. While ferric chloride failed to perform effectively as a coagulant, the other three coagulants were fairly effective. Finally, to further lower the COD of post-coagulation treated water, adsorption using activated carbon was studied. It was found that carbon was effective in reducing the COD of the wastewater using reasonable quantities, where up to 98% COD reduction was achieved using 6 g carbon/L.Key words: textile, wastewater, treatment, coagulation, sedimentation, adsorption.

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)0.001
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 score0.060
Threshold uncertainty score0.101

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.026
GPT teacher head0.233
Teacher spread0.206 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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