Photodynamic Combined with Magnetic Field Applications for Viability Activation of Anaerobic Photosynthetic Bacteria
Bibliographic record
Abstract
This paper reports the influence of light exposure (photodynamic) and magnetic field application on viability activation of anaerobic photosynthetic bacteria (rhodobacter sphaeroides). For photosynthetic process, the rhodobacter sphaeroides have bacteriochlorophyll and carotenoid as major and accessory pigments, respectively. A customized equipment was developed for investigating the effect of light and magnetic field applications on the growth of the bacterial colonies. It was consisted of three main parts, namely a sample holder, an array of light emitting diode (LED) as light source and Helmholtz coils as magnetic field source. The systems of this equipment were controlled by a microntroller of AVR ATMega-8535. Prior to the application in vitro, all LEDs were calibrated, both their intensity and wavelength. After the treatments, all bacteria substances were grown in photosynthetic media (PMS) for 48 hours followed by calculating the number bacterial colonies growth using a total plate count (TPC) method and Quebec colony counter. It was found that the growths of bacterial colonies were influenced by both light intensity and wavelength of LED array. At the same intensities, the wavelength of 430 nm showed highest effect on the growth of bacterial colonies. In addition, upon application of the optimum light combined with magnetic field, the highest growth of bacterial colonies was achieved more than 110% when the optimized light source of energy dose was 204 J/cm2 and magnetic field was 1.8 mT.
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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".