Influence of Temperature on Xylem Nutrient Transport in Plants
Bibliographic record
Abstract
The current study investigates how ambient temperature affects streaming potential-induced electrical energy generation triggered by nutrient flow in the stem xylem.During the experiment, the streaming potential of Brassica juncea is measured at various atmospheric temperatures, and the pressure gradient is computed for numerical simulations.It has been found that as atmospheric temperature rises, the increase in transpiration pull augments both axial and radial flow velocities.This enhances the flow loading at the intersection of the stem xylem core region and the porous pitted wall.Consequently, as atmospheric temperature increases, the mechanical stress inside the pitted porous wall also rises.Furthermore, due to convection-driven ionic transport, it becomes apparent that the magnitude of the induced potential at the bottom side of the stem xylem increases with rising atmospheric temperature.Additionally, owing to the ion-partitioning effect caused by differences in electrical permittivity, the concentration of K appears to be substantially lower in the pitted porous wall.As atmospheric temperature rises, the streaming electric field strengthens, enhancing both electrical and hydraulic power.Interestingly, atmospheric temperature has almost no influence on energy conversion efficiency.The insights drawn from this study contribute to a better understanding of the impact of atmospheric temperature on the development of green energy generation devices with high power densities.
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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".