Fashion Conversation Data on Instagram

The fashion industry is establishing its presence on a number of visual-centric social media like Instagram. This creates an interesting clash as fashion brands that have traditionally practiced highly creative and editorialized image marketing now have to engage with people on the platform that epitomizes impromptu, realtime conversation. What kinds of fashion images do brands and individuals share and what are the types of visual features that attract likes and comments? In this research, we take both quantitative and qualitative approaches to answer these questions. We analyze visual features of fashion posts first via manual tagging and then via training on convolutional neural networks. The classified images were examined across four types of fashion brands: mega couture, small couture, designers, and high street. We find that while product-only images make up the majority of fashion conversation in terms of volume, body snaps and face images that portray fashion items more naturally tend to receive a larger number of likes and comments by the audience. Our findings bring insights into building an automated tool for classifying or generating influential fashion information. We make our novel dataset of {24,752} labeled images on fashion conversations, containing visual and textual cues, available for the research community.Comment: 10 pages, 6 figures, This paper will be presented at ICWSM'1

Ultrahigh energy neutrino scattering: an update

We update our estimates of charged and neutral current neutrino total cross sections on isoscalar nucleons at ultrahigh energies using a global (x, Q^2) fit, motivated by the Froissart bound, to the F_2 (electron-proton) structure function utilizing the most recent analysis of the complete ZEUS and H1 data sets from HERA I. Using the large Q^2, small Bjorken-x limits of the "wee" parton model, we connect the ultrahigh energy neutrino cross sections directly to the large Q^2, small-x extrapolation of our new fit, which we assume saturates the Froissart bound. We compare both to our previous work, which utilized only the smaller ZEUS data set, as well as to recent results of a calculation using the ZEUS-S based global perturbative QCD parton distributions using the combined HERA I results as input. Our new results substantiate our previous conclusions, again predicting significantly smaller cross sections than those predicted by extrapolating pQCD calculations to neutrino energies above 10^9 GeV.Comment: 8 pages, 1 figure, 3 table

Polystyrene-Al2O3 composite solid polymer electrolyte for lithium secondary battery

In a common salt-in-polymer electrolyte, a polymer which has polar groups in the molecular chain is necessary because the polar groups dissolve lithium salt and coordinate cations. Based on the above point of view, polystyrene [PS] that has nonpolar groups is not suitable for the polymer matrix. However, in this PS-based composite polymer-in-salt system, the transport of cations is not by segmental motion but by ion-hopping through a lithium percolation path made of high content lithium salt. Moreover, Al2O3 can dissolve salt, instead of polar groups of polymer matrix, by the Lewis acid-base interactions between the surface group of Al2O3 and salt. Notably, the maximum enhancement of ionic conductivity is found in acidic Al2O3 compared with neutral and basic Al2O3 arising from the increase of free ion fraction by dissociation of salt. It was revealed that PS-Al2O3 composite solid polymer electrolyte containing 70 wt.% salt and 10 wt.% acidic Al2O3 showed the highest ionic conductivity of 9.78 × 10-5 Scm-1 at room temperature