Influence of Keratin on Epoxidized Linseed Oil Curing and Thermoset Performances

The study investigates the synergistic potential of keratin, a protein sourced from chicken feathers, in conjunction with a biobased formulation comprising epoxidized linseed oil (ELO) and dodecenylsuccinic anhydride (DDSA). Through techniques such as differential scanning calorimetry (DSC) and in-situ Fourier transform infrared (FT-IR) spectroscopy, the researchers analyze the influence of keratin on the cross-linking process of ELO, elucidating its chemical role in network formation. Findings reveal that keratin exerts a positive influence on various critical parameters of the network, including its glass transition temperature, storage modulus, and tensile strength. This suggests that the incorporation of keratin enhances the overall performance and mechanical properties of the material. Moreover, the study underscores the potential of keratin as a sustainable resource for developing industrially applicable materials, particularly by repurposing chicken feather waste from the food industry. In essence, the research underscores the promising prospects of utilizing keratin alongside biobased compounds like ELO and DDSA to create sustainable materials with enhanced properties. By harnessing natural proteins in this manner, the study contributes to the advancement of eco-friendly materials with practical industrial applications

Are Word Embedding-based Features Useful for Sarcasm Detection?

This paper makes a simple increment to state-of-the-art in sarcasm detection research. Existing approaches are unable to capture subtle forms of context incongruity which lies at the heart of sarcasm. We explore if prior work can be enhanced using semantic similarity/discordance between word embeddings. We augment word embedding-based features to four feature sets reported in the past. We also experiment with four types of word embeddings. We observe an improvement in sarcasm detection, irrespective of the word embedding used or the original feature set to which our features are augmented. For example, this augmentation results in an improvement in F-score of around 4\% for three out of these four feature sets, and a minor degradation in case of the fourth, when Word2Vec embeddings are used. Finally, a comparison of the four embeddings shows that Word2Vec and dependency weight-based features outperform LSA and GloVe, in terms of their benefit to sarcasm detection.Comment: The paper will be presented at Conference on Empirical Methods in Natural Language Processing (EMNLP) 2016 in November 2016. http://www.emnlp2016.net

Statistical Study of Plasmoids associated with post-CME Current Sheet

We investigate the properties of plasmoids observed in the current sheet formed after an X-8.3 flare followed by a fast CME eruption on September 10, 2017 using Extreme Ultraviolet (EUV) and white-light coronagraph images. The main aim is to understand the evolution of plasmoids at different spatio-temporal scales using existing ground- and space-based instruments. We identified the plasmoids in current sheet observed in the successive images of {\it Atmospheric Imaging Assembly} (AIA) and white-light coronagraphs, K-Cor and LASCO/C2. We found that the current sheet is accompanied by several plasmoids moving upwards and downwards. Our analysis showed that the downward and upward moving plasmoids have average width of 5.92 Mm and 5.65 Mm, respectively in the AIA field of view (FOV). However, upward moving plasmoids have average width of 64 Mm in the K-Cor which evolves to a mean width of 510 Mm in the LASCO/C2 FOV. Upon tracking the plasmoids in successive images, we observe that downward and upward moving plasmoids have average speeds of $\sim$272 km s$^{-1}$ and $\sim$191 km s$^{-1}$ respectively in the EUV passbands. We note that the plasmoids become super-Alfv\'enic when they reach at LASCO FOV. Furthermore, we estimate that the null-point of the current sheet at $\approx$ 1.15 R$_\odot$ where bidirectional plasmoid motion is observed. We study the width distribution of plasmoids formed and notice that it is governed by a power law with a power index of -1.12. Unlike previous studies there is no difference in trend for small and large scale plasmoids. The presence of accelerating plasmoids near the neutral point indicates a longer diffusion region as predicted by MHD models.Comment: Accepted for the publication in Astronomy & Astrophysics (A&A). 10 pages, 11 figures. Animations can be found at https://www.dropbox.com/sh/g0wjq2awxai1hy4/AAClkTHPFkTa5JU-Zulf9a75a?dl=