Flexible synthesis of polyfunctionalised 3-fluoropyrroles

An efficient and selective approach for the synthesis of polyfunctionalised 3-fluoropyrroles has been developed starting from commercial aldehydes. The methodology is concise, efficient and allows for the modular and systematic assembly of polysubstituted 3-fluoropyrroles. This synthesis provides an alternative and highly convergent strategy for the generation of these chemically and biologically important units

On the use of machine learning algorithms in the measurement of stellar magnetic fields

Regression methods based in Machine Learning Algorithms (MLA) have become an important tool for data analysis in many different disciplines. In this work, we use MLA in an astrophysical context; our goal is to measure the mean longitudinal magnetic field in stars (H_ eff) from polarized spectra of high resolution, through the inversion of the so-called multi-line profiles. Using synthetic data, we tested the performance of our technique considering different noise levels: In an ideal scenario of noise-free multi-line profiles, the inversion results are excellent; however, the accuracy of the inversions diminish considerably when noise is taken into account. In consequence, we propose a data pre-process in order to reduce the noise impact, which consists in a denoising profile process combined with an iterative inversion methodology. Applying this data pre-process, we have found a considerable improvement of the inversions results, allowing to estimate the errors associated to the measurements of stellar magnetic fields at different noise levels. We have successfully applied our data analysis technique to two different stars, attaining by first time the measurement of H_eff from multi-line profiles beyond the condition of line autosimilarity assumed by other techniques.Comment: Accepted for publication in A&

Non Catastrophic Endogenous Growth with Pollution and Abatment

When there are pollution externalities the competitive equilibrium is not Pareto-optimal nor environmentally sustainable even if abatment activities are endogenously decided. In this paper we introduce the possibility of an ecological catastrophe like the one predicted by the global climate change, imposing the constraint of an upper-limit to the pollutants stock. We characterize this socially optimal soclution and study conditions for the sustainability of the balanced growth path. We find a trade-off between environmental quality and growth. The rate of growth depends negatively on the weight of environmental care in the utility function and positively on the population growth rate. We show that the emissions reduction recommended in the Kioto protocol is an appropriate policy to avoid the ecological catastrophe and ensure global efficiency and positive long-run growth.Environment; Externalities; Optimal Growth, Ecological Catastrophe; Sustainability