Advanced Nano-biotechnology for Chlorinated Volatile Compound Pollutants Control
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Volatile organic compounds (VOCs) include different organic chemicals that can be easily vaporized and transported long distances via the environment. VOCs and health effects are dependent on the type, concentrations and duration of exposure. Chlorinated volatile compounds (CVOCs) are the most toxic VOCs because of their potential to cause cancer in humans. Many CVOCs are present in significant amounts in our ecosystems, including air, water and soil, and are resistant to degrade, despite the fact that their use has recently been more carefully managed and restricted. These chlorinated compounds are highly toxic and numerous have been banned from commercial utilization because they are persistent in the environment and accumulate in biological systems. Although these chemicals have been banned for decades, they are still being measured in the environment and the food chain. This paper provides a comprehensive review of the recent applications of biotechnology and nanotechnology in CVOCs remediation in various environmental systems. It is divided into many sections; each focuses on specific subtopics, covering diverse perspectives on the principal topic. Sections presented in the paper include; occurrence of CVOCs in the environment, sources, potential human health effects, recent biotechnology and nanotechnology used for CVOCs remediation, advantages and disadvantages of each strategy of treatment and future perspectives in this aspect are also provided. Finally, this paper presents advanced technologies available, to remind CVOCs emissions with their relative merits and demerits, better understand this integrated technology, and to effectively apply them in air, soil, and groundwater remediation. Consequently, we hope that this paper will guide and inspire the application of biotechnology and nanotechnology to the remediation of CVOCs.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it