Active Fluids in Environment
Bibliographic record
Abstract
Photosynthetic carbon capture by trees and other vegetation is believed to be among the most efficient and environmentally friendly strategies to reduce CO2 concentration in the earth atmosphere. The 2018 IPCC special report suggests that 1 billion hectares of new forest is necessary to limit global warming to 1.5 C by 2050. However, recent studies estimate that only 0.9 billion hectares of land are available on the earth outside of cropland and urban regions for potential forest restoration. Water availability can also be one of limitations of this strategy. Biofixation of carbon dioxide by aqueous suspensions of bacteria and algae (referred to as living or active fluids) is an alternative solution for limitation of CO2. Biofixation is 10-15 times more efficient than trees and produces biomass that has value in producing biofuels, human nutritional supplements, cosmetic products, biofertilizers and animal feed. These microorganisms are cultivated in dedicated reactors commonly referred to as photobioreactors (PBR). The physical phenomena occurring in PBR involve a sophisticated nonlinear interaction between the hydrodynamics of active fluids, biokinetic processes, radiative transfer as well as heat and mass transfer in microorganism suspensions. A high degree of success in the design and optimization of PBR therefore, relies on the proper understanding and modelling of physical properties and rheological behavior of cell suspensions. Active fluids, like suspensions of autonomous fluid particles, can show unexpected manifestations. In a recent study we showed the diffusion coefficient of cell suspensions on solid surfaces reduces with time; this reduction is directly related to the contact history between the cell and the surface. We also showed that this diffusion is a function of surface stiffness (durotaxis) and light intensity and direction (phototaxis). In our most recent study, we have focused on the new measurements of the physical properties, rheological behavior and biomass, lipid and pigment production of Synechocystis, an environmentally important model bacterium, under flow shear stress. This information is of primordial importance in hydrodynamical and radiative design of high performance photobioreactors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.017 |
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".