Constraining differential renormalization in abelian gauge theories

We present a procedure of differential renormalization at the one loop level which avoids introducing unnecessary renormalization constants and automatically preserves abelian gauge invariance. The amplitudes are expressed in terms of a basis of singular functions. The local terms appearing in the renormalization of these functions are determined by requiring consistency with the propagator equation. Previous results in abelian theories, with and without supersymmetry, are discussed in this context.Comment: 13 pages, LaTeX. Some equations corrected and a reference added. Complete ps paper also available at http://www-ftae.ugr.es/papiros.html or ftp://ftae3.ugr.es/pub/rmt/ugft73.p

Nonparametric maximum likelihood estimation of probability densities by penalty function methods

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates

Mechanical Unfolding of a Simple Model Protein Goes Beyond the Reach of One-Dimensional Descriptions

We study the mechanical unfolding of a simple model protein. The Langevin dynamics results are analyzed using Markov-model methods which allow to describe completely the configurational space of the system. Using transition path theory we also provide a quantitative description of the unfolding pathways followed by the system. Our study shows a complex dynamical scenario. In particular, we see that the usual one-dimensional picture: free-energy vs end-to-end distance representation, gives a misleading description of the process. Unfolding can occur following different pathways and configurations which seem to play a central role in one-dimensional pictures are not the intermediate states of the unfolding dynamics.Comment: 10 pages, 6 figure

Investor protection and corporate control

We argue that investor protection changes the relative importance of productivity and scale as drivers of corporate control transfers. Using a large sample of European firms we find that control transfers are more correlated with increasing profitability and less correlated with increasing size when investor protection is strong. This suggests that improving productivity is more important as a driver of acquisitions when investor protection is strong, and alleviating financial constraints or empire building are more important when investor protection is weak. Our evidence is consistent with the idea that good investor protection promotes a more productive use of corporate assets