Composite Materials from Natural Resources: Recent Trends and Future Potentials
Bibliographic record
Abstract
Bast fibre / stem fibre Jute fibre: Generally jute fibres are extracted from the ribbon of the stem.It is used as packaging material (bags), carpet backing, ropes, and yarns (Fig 2.1.1a)and in many other decorative items. 2.Leaf fibre Sisal: Sisal plant belongs to the agave family (Agavaceae).The plant looks like giant pineapples.The soft tissue is scraped from the fibres by manually or machine (Fig 2.1.1b).It is mainly used for mats, carpets and many other reinforcement materials.Hemp: Hemp fibres have long been valued for their high strength and long fibre length, and have been used extensively in the fabrication of ropes and sails, as well as for paper and textiles.Hemp is a hardy plant, and grows well in a moderately cool climate.Hemp fibres are mainly composed of cellulose, hemicellulose, and lignin and pectin (Fig 2.1.1c).Ramie: Ramie is an expensive and durable fibre.The ramie plant can easily grow in fabrics.It is widely used in making of furniture covers and wall paper etc.Cotton: Cotton is the most important fibre used in the textile industry.Cotton is generally collected by picking which is generally carried out by hand.Comparison with other natural fibres, cotton is mainly used in the manufacturing of clothes, blankets, carpets (Fig 2.1.1d). 3. Seed fibreFlax: Flax fibre one of the strongest fibre among natural fibre.Flax has good heat conducting properties.However, constant creasing in the same place in sharp folds tends to break the fibre.Flax is used for the production of linen, canvas, ropes and sacks.4. Fruit fibresCoir: Generally coconut fibres (Fig 2.1.1e)are obtained from the husk of the fruit of the coconut palm.These coconut fibres are strong, light and easily withstand heat and salt water.5. Stalk fibreThese fibres are actually extracted from the stalks of the plant.For example, rice, barley, straws of wheat, bamboo and grass. How to referenceIn order to correctly reference this scholarly work, feel free to
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".