Modification of the electrokinetic motion of microalgae through light illumination for viability assessment
Bibliographic record
Abstract
The viability detection of microalgae with the electrokinetic (EK) technique shows vast applications in the biology and maritime industry. However, due to the slight variations in the EK properties between alive and dead microalgae cells, the accuracy and practicability of this technique is limited. In this paper, the light illumination pretreatment was conducted to modify the EK velocity of microalgae for enhancing the EK difference. The effects of the illumination time and light color on the EK velocities of Chlorella vulgaris and Isochrysis galbana were systematically measured, and the EK differences between alive and dead cells were calculated and compared. The results indicate that under light illumination, the photosynthesis of the alive cells leads to the amplification of the zeta potential, leading toward increase in the EK difference along with the illumination time. By using light with different color spectra to treat the microalgae, it was found that the EK difference changes with the light color according to the following order: white light > red light > blue light > green light. The difference in EK potential with exposure to white light treatment surpasses over 10-fold in comparison to those without such treatment. The light pretreatment technique, as illustrated in this study, offers an advantageous strategy to enhance the EK difference between living and dead cells, proving beneficial in the field of microalgae biotechnology.
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How this classification was reachedexpand
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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".