Trends in income inequality in the European Union: implications for health inequalities

The comparative analysis of income inequality across countries has acquired increasing importance in recent years. This paper is divided in two parts. The first one is focused on the analysis of income inequality in the European Union. To carry out this task, we use different models based on Lorenz curves and quantiles functions and different equivalence scales. The European Community Household Panel Data are used. The second part of the paper is focused on explaining the differences in income and health inequalities across European countries. In particular several hypotheses concerning the economic determinants of health inequalities are studied. KEY WORDS Income inequality, Lorenz curves, quantile functions, equivalence scales, European Community Household Panel, health inequalities

Ammonia observations of the nearby molecular cloud MBM 12

We present NH3(1,1) and NH3(2,2) observations of MBM 12, the closest known molecular cloud (65 pc distance), aimed to find evidence for on-going star formation processes. No local temperature (with a T_rot upper limit of 12 K) nor linewidth enhancement is found, which suggests that the area of the cloud we mapped (~ 15' size) is not currently forming stars. Therefore, this close ``starless'' molecular gas region is an ideal laboratory to study the physical conditions preceding new star formation. A radio continuum source was found in Very Large Array archive data, close but outside the NH3 emission. This source is likely to be a background object.Comment: 8 pages, 3 figures, accepted by MNRA

Single magnetic adsorbates on s-wave superconductors

In superconductors, magnetic impurities induce a pair-breaking potential for Cooper pairs, which locally affects the Bogoliubov quasiparticles and gives rise to Yu-Shiba-Rusinov (YSR or Shiba, in short) bound states in the density of states (DoS). These states carry information on the magnetic coupling strength of the impurity with the superconductor, which determines the many-body ground state properties of the system. Recently, the interest in Shiba physics was boosted by the prediction of topological superconductivity and Majorana modes in magnetically coupled chains and arrays of Shiba impurities. Here, we review the physical insights obtained by scanning tunneling microscopy into single magnetic adsorbates on the $s$-wave superconductor lead (Pb). We explore the tunneling processes into Shiba states, show how magnetic anisotropy affects many-body excitations, and determine the crossing of the many-body groundstate through a quantum phase transition. Finally, we discuss the coupling of impurities into dimers and chains and their relation to Majorana physics.Comment: 18 pages, 17 figures, revie

Tuning the magnetic anisotropy of single molecules

The magnetism of single atoms and molecules is governed by the atomic scale environment. In general, the reduced symmetry of the surrounding splits the $d$ states and aligns the magnetic moment along certain favorable directions. Here, we show that we can reversibly modify the magnetocrystalline anisotropy by manipulating the environment of single iron(II) porphyrin molecules adsorbed on Pb(111) with the tip of a scanning tunneling microscope. When we decrease the tip--molecule distance, we first observe a small increase followed by an exponential decrease of the axial anisotropy on the molecules. This is in contrast to the monotonous increase observed earlier for the same molecule with an additional axial Cl ligand. We ascribe the changes in the anisotropy of both species to a deformation of the molecules in the presence of the attractive force of the tip, which leads to a change in the $d$ level alignment. These experiments demonstrate the feasibility of a precise tuning of the magnetic anisotropy of an individual molecule by mechanical control.Comment: 16 pages, 5 figures; online at Nano Letters (2015

Unexpected Event Prediction in Wire Electrical Discharge Machining Using Deep Learning Techniques

Theoretical models of manufacturing processes provide a valuable insight into physical phenomena but their application to practical industrial situations is sometimes difficult. In the context of Industry 4.0, artificial intelligence techniques can provide efficient solutions to actual manufacturing problems when big data are available. Within the field of artificial intelligence, the use of deep learning is growing exponentially in solving many problems related to information and communication technologies (ICTs) but it still remains scarce or even rare in the field of manufacturing. In this work, deep learning is used to efficiently predict unexpected events in wire electrical discharge machining (WEDM), an advanced machining process largely used for aerospace components. The occurrence of an unexpected event, namely the change of thickness of the machined part, can be effectively predicted by recognizing hidden patterns from process signals. Based on WEDM experiments, different deep learning architectures were tested. By using a combination of a convolutional layer with gated recurrent units, thickness variation in the machined component could be predicted in 97.4% of cases, at least 2 mm in advance, which is extremely fast, acting before the process has degraded. New possibilities of deep learning for high-performance machine tools must be examined in the near future.The authors gratefully acknowledge the funding support received from the Spanish Ministry of Economy and Competitiveness and the FEDER operation program for funding the project "Scientific models and machine-tool advanced sensing techniques for efficient machining of precision components of Low Pressure Turbines" (DPI2017-82239-P) and UPV/EHU (UFI 11/29). The authors would also like to thank Euskampus and ONA-EDM for their support in this project

Magnetic anisotropy in Shiba bound states across a quantum phase transition

The exchange coupling between magnetic adsorbates and a superconducting substrate leads to Shiba states inside the superconducting energy gap and a Kondo resonance outside the gap. The exchange coupling strength determines whether the quantum many-body ground state is a Kondo singlet or a singlet of the paired superconducting quasiparticles. Here, we use scanning tunneling spectroscopy to identify the different quantum ground states of Manganese phthalocyanine on Pb(111). We observe Shiba states, which are split into triplets by magnetocrystalline anisotropy. Their characteristic spectral weight yields an unambiguous proof of the nature of the quantum ground state.Comment: 6 pages, 4 figure

THE EXPLANATORY POWER OF TRUST AND COMMITMENT AND STAKEHOLDERS’ SALIENCE: THEIR INFLUENCE ON THE REVERSE LOGISTICS PROGRAMS PERFORMANCE

There is a growing awareness among practitioners and scholars regarding the importance of Relationship Marketing and its advantages in the supply chain management context. This is particularly appropriate for Reverse Logistics (RL) activities, which are characterized by several relationships between different stakeholders and the firm. Drawing on multiple theoretical approaches, we propose that RL programs result from the combination of external, organizational, and individual factors. We emphasize the role of trust and commitment as key influential elements on the RL systems implementation and their subsequent performance.