Estimating US persistent and transitory monetary shocks: implications for monetary policy

This paper proposes an estimation method for persistent and transitory monetary shocks using the monetary policy modeling proposed in Andolfatto et al, [Journal of Monetary Economics, 55 (2008), pp.: 406-422]. The contribution of the paper is threefold: a) to deal with non-Gaussian innovations, we consider a convenient reformulation of the state-space representation that enables us to use the Kalman filter as an optimal estimation algorithm. Now the state equation allows expectations play a significant role in explaining the future time evolution of monetary shocks; b) it offers the possibility to perform maximum likelihood estimation for all the parameters involved in the monetary policy, and c) as a consequence, we can estimate the conditional probability that a regime change has occurred in the current period given an observed monetary shock. Empirical evidence on US monetary policy making is provided through the lens of a Taylor rule, suggesting that the Fed’s policy was implemented accordingly with the macroeconomic conditions after the Great Moderation. The use of the particle filter produces similar quantitative and qualitative findings. However, our procedure has much less computational cost.Kalman filter, Non-normality, Particle filter, Monetary policy

Sensores inteligentes : la revolución tecnológica de la instrumentación

Peer Reviewe

A Decomposition-Ensemble framework for oil price forecasting during Covid19 outbreak: enabling rapid response in IOCs and NOCs

One of main economic impacts of Covid19 was the unprecedented drop in crude futures prices. After the crash, a high-volatility period followed, adding more uncertainty to the markets and financial institutions worldwide. Oil Companies rely on oil price projections for trading activities as well as financial and operational planning. We propose a decomposition-ensemble framework based on CEEMDAN algorithm and Adaptive Trees to forecast oil prices with the aim of reducing uncertainty and enabling rapid response in IOC/NOC¿s trading, planning, and operations

In Silico Design and Selection of CD44 Antagonists:implementation of computational methodologies in drug discovery and design

Drug discovery (DD) is a process that aims to identify drug candidates through a thorough evaluation of the biological activity of small molecules or biomolecules. Computational strategies (CS) are now necessary tools for speeding up DD. Chapter 1 describes the use of CS throughout the DD process, from the early stages of drug design to the use of artificial intelligence for the de novo design of therapeutic molecules. Chapter 2 describes an in-silico workflow for identifying potential high-affinity CD44 antagonists, ranging from structural analysis of the target to the analysis of ligand-protein interactions and molecular dynamics (MD). In Chapter 3, we tested the shape-guided algorithm on a dataset of macrocycles, identifying the characteristics that need to be improved for the development of new tools for macrocycle sampling and design. In Chapter 4, we describe a detailed reverse docking protocol for identifying potential 4-hydroxycoumarin (4-HC) targets. The strategy described in this chapter is easily transferable to other compounds and protein datasets for overcoming bottlenecks in molecular docking protocols, particularly reverse docking approaches. Finally, Chapter 5 shows how computational methods and experimental results can be used to repurpose compounds as potential COVID-19 treatments. According to our findings, the HCV drug boceprevir could be clinically tested or used as a lead molecule to develop compounds that target COVID-19 or other coronaviral infections. These chapters, in summary, demonstrate the importance, application, limitations, and future of computational methods in the state-of-the-art drug design process

Experimental study for the determination of the turbulence onset in natural convection on inclined plates

In June, 8th, 2009 the balloon-borne solar telescope SUNRISE was launched from the Swedish Space Corporation balloon facility Esrange. A telescope with a mirror of 1 m in diameter ob-served the Sun during six days until the mission was terminated in Canada. The design process of SUNRISE and of any optical telescope requires the analysis of the effect of surrounding air on the quality of images. The turbulence encountered in the local telescope environment de-grades its optical performance. This phenomenon called `seeing' consists of optical aberrations produced by density non-homogeneities in the air along the optical path. The refraction index of air changes due to thermal non-uniformities so that the wavefront incident on the mirror is randomly distorted, and therefore, images are altered. When telescope mirrors are heated, as it happens in solar telescopes, and therefore they are at a temperature different from the environment's, natural convection occurs. It is then crucial to know whether the flow in front of the mirror is laminar or turbulent. After reviewing the literature, it was found that the scattering of results about the onset of the transition gives only rough orders of magnitude of the values of the critical Grashof numbers. Aiming to obtain more information about it, the problem of determination of the turbulence onset in natural convection on heated inclined plates in air environment was experimentally revisited. The transition has been determined from hot wire velocity measurements. The onset of turbulence has been considered to take place where velocity perturbations start to grow. Experiments have shown that the onset depends not only on the Grashof number, but also on other parameters as the temperature difference between the heated plate and the surrounding air. A correlation between dimensionless Grashof and Reynolds numbers has been obtained, fitting extraordinarily well the experimental data. The results are obtained in terms of non-dimensional numbers, this way they apply to any air pressure and therefore to any floating altitud

Characterization of AtDGK2 in relation to Contact Sites

Contact Sites are conserved cellular regions where two membranes of different organelles are very close but not merged. Contact sites between the endoplasmic reticulum (ER) and the plasma membrane (ER-PM CS) play important roles in metabolic functions. We have identified AtDGK2 (Diacylglycerol kinase 2) as an interactor of SYT1 (Synaptotagmin1), which is a protein located at ER-PM CS. DGKs phosphorylate diacylglycerol to produce phosphatidic acid, both important signalling molecules. Arabidopsis thaliana has seven AtDGKs, but only AtDGK1 and AtDGK2 present an ER transmembrane domain, the rest are cytoplasmic. We have analysed the subcellular localization and functions of these two proteins.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. BIO2017-82609-

Factors that influence the behavior of a person against the risk of starting a business in Latin America

El desempleo y la baja calidad de los empleos existentes, han creado la necesidad de emprender y pasar de ser empleado a emprendedor. Sin embargo, existen algunos factores que caracterizan a este comportamiento. La presente investigación identifica algunos de los factores que incrementan en una persona el riesgo de emprender un negocio en América Latina. Los principales factores que influyen en este comportamiento son: la experiencia, el conocimiento, la habilidad y la edad entre las once variables utilizadas en el periodo 2009-2011. Los modelos de redes neuronales utilizados clasifican a la variable dependiente (miedo al fracaso) con un porcentaje de acierto del 68% en el periodo de estudi

Networks and Narratives on Twitter about the #8M International Women's Day (2018) in Spain: Feminist Social Movement and counter-movement expressions

[EN] On March 8, 2018, International Women's Day took place worldwide, which brought relevant mobilisations and support in Spain. The feminist movement proved strong and demonstrated great vitality in a historic and unprecedented mobilisation. That day, many people took to the streets worldwide, and massively in Spain, to demand equal rights and opportunities for women and men. This mobilisation also took place on social networks. This paper aims to analyse the networks and narratives on Twitter around March 8 virtual mobilisation in Spain in 2018. This work analyses 557,548 tweets containing the hashtags representative of the mobilisation and collected through the API rest and API streaming Twitter platforms. The results suggest the presence of a strong national and international network of support for the feminist movement and a counter-feminist network that does not support the mobilisation and also propagates hate speech towards women and the feminist movement itself on the Twitter network.Grant PID2021-123983OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. ESEIS (SEJ-216)/COIDESO Centers and EPIT2023 from University of Huelva. Ayuda predoctoral para la Formación de Profesorado Universitario(FPU20/02848)Ruiz-Angel, E.; Ruiz-Angel, P.; Santos, FJ.; Gualda, E. (2023). Networks and Narratives on Twitter about the #8M International Women's Day (2018) in Spain: Feminist Social Movement and counter-movement expressions. Editorial Universitat Politècnica de València. 203-204. http://hdl.handle.net/10251/20178620320