In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made available to the research community with the goal of enabling better text analysis of Hindi English CSMT. The pipeline is accessible at 1 .

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A crosslink-able elastomeric polyester urethane (PEU) was blended with a thermoplastic, polyacrylonitrile (PAN), and electrospun into nanofibers. The effects of the PEU/PAN ratio and the crosslinking reaction on the morphology and the tensile properties of the as-spun fiber mats were investigated. With the same overall polymer concentration (9 wt %), the nanofiber containing higher composition of PEU shows a slight decrease in the average fiber diameter, but the tensile strength, the elongation at break and tensile modulus of the nanofiber mats are all improved.These tensile properties are further enhanced by slight crosslinking of the PEU component within the nanofibers.

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