'Thinking of Spain in a flat way:' visiting Spain and Spanish cultural heritage through contemporary Japanese anime

This article contextualizes the representation of Spain and Spanish culture among Japanese cultural producers, particularly through the production of Japanese commercial animation (commonly named anime). Toward that goal, it provides a historical background of Japan-Spain relations within the context of the tourism industry, as well as some examples of the diverse forms of representation within several creative industries. Subsequently, the article reviews the ways in which popular culture has been contributed to national branding. There is special attention to the Spanish case and the proliferation of such images sometimes resulting in the (mis)representation of Spain's tangible and intangible cultural heritage. Internationally-distributed anime productions will be examined as a reflection of Spanish national branding on Japanese audiences and this global industry. Three cases among contemporary anime productions have been selected due to the combination of fictional and misrepresented Spanish cultural features in their narratives

Physical (ir)relevance of ambiguities to Lorentz and CPT violation in QED

We discuss the regularization and renormalization of QED with Lorentz and CPT violation, and argue that the coefficient of the Chern-Simons term is an independent parameter not determined by gauge invariance. We also study these issues in a model with spontaneous breaking of Lorentz and CPT symmetries and find an explicit relation with the ABJ anomaly. This explains the observed convergence of the induced Chern-Simons term.Comment: 16 pages, references adde

Learning how to be robust: Deep polynomial regression

Polynomial regression is a recurrent problem with a large number of applications. In computer vision it often appears in motion analysis. Whatever the application, standard methods for regression of polynomial models tend to deliver biased results when the input data is heavily contaminated by outliers. Moreover, the problem is even harder when outliers have strong structure. Departing from problem-tailored heuristics for robust estimation of parametric models, we explore deep convolutional neural networks. Our work aims to find a generic approach for training deep regression models without the explicit need of supervised annotation. We bypass the need for a tailored loss function on the regression parameters by attaching to our model a differentiable hard-wired decoder corresponding to the polynomial operation at hand. We demonstrate the value of our findings by comparing with standard robust regression methods. Furthermore, we demonstrate how to use such models for a real computer vision problem, i.e., video stabilization. The qualitative and quantitative experiments show that neural networks are able to learn robustness for general polynomial regression, with results that well overpass scores of traditional robust estimation methods.Comment: 18 pages, conferenc

There's Something Happening Here: A Look at The California Endowment's Building Healthy Communities Initiative

In 2011, TCE commissioned PERE to help capture some of the dynamism happening in each of the sites as they were pivoting from the initial planning phase, which started in 2009, to early implementation.Our focus was on the over-arching story of BHC rather than on the narrative of each site, which would have required many more interviews, many more site visits, and many, many more pages to convey. And while we touch on some of the interactions between BHC and the communications and policy work done under the statewide umbrella of Health Happens Here, our emphasis in this report is on BHC and the sites themselves.Through the course of this research, we have become increasingly convinced that TCE is indeed onto something -- if not big, at least important. In order to clarify exactly what it is, we use a simplifying three-part storyline linked together by an overarching concept of Just Health