Evolution of singlet structure functions from DGLAP equation at next-to-next-to-leading order at small-x

A semi-numerical solution to Dokshitzer- Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equations at leading order (LO), next-to-leading order (NLO) and next-to-next-to-leading order (NNLO) in the small-x limit is presented. Here we have used Taylor series expansion method to solve the evolution equations and, t- and x-evolutions of the singlet structure functions have been obtained with such solution. We have also calculated t- and x-evolutions of deuteron structure functions F_2^d, and the results are compared with the E665 data and NMC data. The results are also compared to those obtained by the fit to F_2^d produced by the NNPDF collaboration based on the NMC and BCDMS data.Comment: 26 pages, 6 figure

How Does Identifying as Gluten-Free Impact Information Choice Regarding the Gluten-Free Diet?

The market for gluten-free products is a multi-billion-dollar industry in the United States and has seen tremendous growth in the recent years. The retail sales of gluten-free foods in the United States almost tripled between 2011 and 2015, although rates of diagnosed gluten-related health problems have not risen. In addition to people who suffer from Celiac Disease, Wheat Allergy and Non-Celiac Gluten Sensitivity, there is a category or people known as PWAG (people who avoid gluten) who seem to have significantly contributed to this boom in the market for gluten-free foods. With more people choosing to adopt the gluten-free diet, there might be a negative effect for people who genuinely need to adhere to the gluten-free diet for medical reasons. An increase in the number of PWAG may be attributable in part to the bias that people have for “free-from” food labels, believing them to be healthier. Such beliefs among people arise due to selective information seeking and avoidance behaviors. Beliefs can act as self-regulatory measures to form various identities among individuals. In this study, we examine how identifying as gluten-free influences the valence of information (positive, negative, both positive and negative) about the gluten-free diet that people choose to read. We developed a survey which was administered online by the survey firm IRI. Only people who had previously tried to reduce/avoid gluten from their diets or are currently on a reduced-gluten/gluten-free diet were considered for the study. The results from a logistic regression model indicated that if an individual identifies as gluten-free, she is more likely to read about the benefits of following a gluten-free diet, though the result is not significant at normal levels, which may be due to small sample sizes. Advisor: Christopher R. Gustafso