Bibliographic record
Abstract
The article highlights some recent trends in the bleaching of textile materials. An attempt has been made to compare the effect of electrochemical bleaching with conventional bleaching of cotton. Electric current is used in the preparation of a bleaching agent to replace bleaching powder. The sodium hypochlorite generated from electrolyte cell is sufficient to produce powerful bleaching agent with available chlorine. Electrochemical bleaching with sodium hypochlorite offers numerous advantages like prevention of effluent problem, economy, reliability, cleanliness, and convenience in working. Attempts have been made to use sodium perborate as a bleaching agent with potassium persulphate as an activator at lower temperature in combined pre treatment of cotton fabric. Experimental trials have been designed by using taguchi technique. This bleaching technique promises to be eco-friendly process. In yet another interesting work, effort has been taken to bleach the scoured cotton fabric with sodium perborate as bleaching agent and tetreacetyl ethylenediamine as bleaching activator. The concentrations of these chemicals, temperature and time of the treatment have been varied. The utilization of hydrogen peroxide is much higher as compared with that of conventional bleaching process. Other advantages include less requirement of water and energy, thereby satisfying needs of eco-friendly process, lesser loss in weight, tearing strength, and tensile strength, in comparison with conventional bleaching process without compromising whiteness index.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".