A mathematical model of the locomotion of bacteria near an inclined solid substrate: effects of different waveforms and rheological properties of couple-stress slime
Bibliographic record
Abstract
Morphological mutations in bacterial cell make them the most miscellaneous microscopic group. Their non-flagellated species known as gliding bacteria exhibit self-powered motion and leave an adhesive trail of slime. The self-propelled motion in some gliding bacteria is achieved as a result of backward surface wave in the cell envelope. Motivated by this fact, an undulating surface on a layer of couple-stress fluid is used to model the motion of such gliding bacteria. Five different wave profiles, namely, sawtooth, sinusoidal, triangular, trapezoidal, and square profiles are used to model the waveform of the undulating wave in the outer cell surface. The inclination of the surface is also integrated into the model. The flow equations are set up under the lubrication assumption. Stream function is derived as an elementary function of an organism’s speed, undulation amplitude, and couple-stress parameter with its flow rate. Speed of the glider and flow rate (satisfying equilibrium conditions) are computed by employing modified Newton–Raphson method. These refined values are further utilized to compute the power dissipation. Effects of different waveforms, inclination angle, gravitational and couple-stress parameters on the speed of the microorganism and rate of energy expended are also quantified. Slime velocity is also plotted for fixed glider. In addition, making use of the obtained realistic set of values of the organism’s speed, flow rate, occlusion parameter, and couple-stress parameter, streamline patterns of the slime are plotted and discussed in detail.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".