Power Plant Algal Treatment with Focus on the Sonication of Enteromorpha Prolifera Macro Algae
Bibliographic record
Abstract
While others considering algae as the “light of hoop” to the energy crisis, and as a carbon neutral technology to combat global warming, uncontrolled growth and its eutrophication can be considered a challenging pollution issue. Nevertheless, in the last a few decades algae pollution has become a global issue. The occurrence of algal bloom in water source has posed a serious water safety and unaccounted control and maintenance at substantial added cost. Overgrowing algae have brought negative impacts on power plant and less frequently led to shutdown of the desalination or power plant. The eutrophication which is rarely is eliminated; it could be controlled by mechanical filtration and chemical biocidal methods. This adds another economic burden by the supply of chemical and their neutralizing agent to cope with tight EPA limits. In this work a review of the treatment of algae is carried out which involves chemical, mechanical, electromechanical and as well as the aid of scavengers directly or indirectly and their combination. As plausible results on the sonication treatment have been emerging, recent work of the author was presented as well to show the effectiveness of the sonication technology in the treatment of the Enteromorpha Prolifera Macro Algae.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".