Control of bacteria movement by using photo responsive media
Bibliographic record
Abstract
Liquid crystalline materials have been shown to be an excellent host matrix enabling the easy observation of bacteria movements. In some cases, even the high sensitivity of such matrix was used to control materials’ properties by bacteria. Motivated by the key role played by bacteria in the health and food industries, our group is working on the development of dynamic micro control techniques by using photosensitivity of azobenzene or DSCG molecules. We think that the capability to control their movement may be useful for many applications, and, in the present work, we explore the possibility of such active control of the movement of flagellated bacteria (a bacterium that can swim thanks to the rotation of its helix). We demonstrate that we can dynamically change the swimming direction of bacteria by incorporating them into a liquid crystal where the phase transition is locally controlled by UV illumination. We shall also mention briefly about other types of control (magnetic, isomeriz)
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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) | 0.005 | 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".