Characterisation of macrogel composition from industrial natural rubber samples: Influence of proteins on the macrogel crosslink density

The insoluble (macrogel) and soluble fractions of 11 commercial natural rubber (NR) samples (Technically specified rubber) were separated. Nitrogen titrations and lipid extractions enabled a quantitative assessment of the proteins and extractable lipids in each fraction. Swelling was measured in tetrahydrofuran in order to evaluate the crosslink density (Mc –1) of each macrogel. While the soluble fraction had a high lipid concentration, the majority of non-isoprene compounds of the macrogel were found to be proteins, which accounted for 4.6 to 50.8% (w/w) of the macrogel. Indeed, the macrogels contained less than 0.5% (w/w) extractable lipids. However, our results showed that the soluble fraction contained large quantities of proteins (16–66% of the nitrogen content of the raw NR sample), probably structuring microaggregates. An exponential correlation (R2 > 0.96) was found between the crosslink density and the protein concentration of macrogel, suggesting that proteins are involved in the majority of crosslinks in macrogel. (Résumé d'auteur

Simulation-based high resolution fire danger mapping using deep learning

Wildfire occurrence and behavior are difficult to predict very locally for the next day. In the present work, we use an artificial neural network emulator called DeepFire, trained on the basis of simulated fire sizes, and study its application to fire danger mapping using actual weather fore-1 casts. Experimental analysis is based on DeepFire forecasts for 13 relatively big fires that occurred in Corsica and corresponding forecasts based on a fire danger index used in operational conditions. A comparative analysis of both indices is presented, highlighting the differences in terms of precision and expected results of such predictions. Forcing weather forecasts used as input have high spatial resolution and high frequency, which also applies to the fire danger predictions. Additionally, input uncertainty is propagated through DeepFire, resulting in ensembles of emulated fire size. Eventually, several approaches are proposed to analyze the results and help in investing assessment of next-day fire danger using this new simulation-based prediction system

Relationship between Angular Measurements and Facial Shape of Young Ivorians with Normal Dental Occlusion

Objective. The aim of this study was to perform an analysis of angular measurements (from both the full face and profile), according to shapes of the human face. Method. It was a descriptive and cross-sectional study of 108 black Ivorian subjects. For each subject selected, two standardized photographs (full face and profile) were taken, followed by anthropometric measurements. The data collected were analyzed using the SPSS 20.0 statistics software for Windows. Results. In the present work, the faces were considered according to three particular qualifiers: broad face, medium face, and narrow face. Thus, 45.37% of the faces in this study were large, 31.48% on average, and 23.15% narrow. The interlabial angles of average face and long face were wider than that of large face with p<0.01. The angle of the facial width was higher for large face and average face, compared to narrow face (p<0.001). Conclusion. Median and bilateral angles lead to rational understanding of the various shapes of the human face