Collisionless Hydrodynamics of Doped Graphene in a Magnetic Field

The electrodynamics of a two-dimensional gas of massless fermions in graphene is studied by a collisionless hydrodynamic approach. A low-energy dispersion relation for the collective modes (plasmons) is derived both in the absence and in the presence of a perpendicular magnetic field. The results for graphene are compared to those for a standard two-dimensional gas of massive electrons. We further compare the results within the classical hydrodynamic approach to the full quantum mechanical calculation in the random phase approximation. The low-energy dispersion relation is shown to be a good approximation at small wave vectors. The limitations of this approach at higher order is also discussed.Comment: 7 pages, 1 figur

Effect of Point Defects on the Optical and Transport Properties of MoS2 and WS2

Imperfections in the crystal structure, such as point defects, can strongly modify the optical and transport properties of materials. Here, we study the effect of point defects on the optical and DC conductivities of single layers of semiconducting transition metal dichalcogenides with the form $M$S$_2$, where $M$=Mo or W. The electronic structure is considered within a six bands tight-binding model, which accounts for the relevant combination of $d$ orbitals of the metal $M$ and $p$ orbitals of the chalcogen $S$. We use the Kubo formula for the calculation of the conductivity in samples with different distributions of disorder. We find that $M$ and/or S defects create mid-gap states that localize charge carriers around the defects and which modify the optical and transport properties of the material, in agreement with recent experiments. Furthermore, our results indicate a much higher mobility for $p$-doped WS$_2$ in comparison to MoS$_2$

A Convolutional Neural Network for the Automatic Diagnosis of Collagen VI related Muscular Dystrophies

The development of machine learning systems for the diagnosis of rare diseases is challenging mainly due the lack of data to study them. Despite this challenge, this paper proposes a system for the Computer Aided Diagnosis (CAD) of low-prevalence, congenital muscular dystrophies from confocal microscopy images. The proposed CAD system relies on a Convolutional Neural Network (CNN) which performs an independent classification for non-overlapping patches tiling the input image, and generates an overall decision summarizing the individual decisions for the patches on the query image. This decision scheme points to the possibly problematic areas in the input images and provides a global quantitative evaluation of the state of the patients, which is fundamental for diagnosis and to monitor the efficiency of therapies.Comment: Submitted for review to Expert Systems With Application

Do tolerant societies demand better institutions?

The increasing ethnic heterogeneity that many societies are experiencing could be interpreted as a detrimental phenomenon, since empirical literature exists that indicates that higher levels of ethnic fractionalization induce higher levels of corruption. This paper aims to show the role of tolerance in overcoming this harmful effect of ethnic heterogeneity. To this end, a sample of 86 countries is tested for a positive association between ethnic fractionalization and corruption. It is then shown that tolerance offsets this effect through both direct and indirect effects on corruption. In order to analyse the indirect effects, the level of income and the freedom of the press are selected as channels, since these represent two determinants of corruption that are linked to tolerance. Moreover, tolerance and corruption have been modelled as composites. Consequently, Partial Least Squares path modelling (PLS-PM) has been used. For our sample, an index of tolerance towards immigrants and people of different race and an index of corruption are constructed, for which several sources are jointly utilised. Our results appear to indicate that the adverse effect of ethnic fractionalization on corruption is offset by tolerance, which reduces corruption not only directly but also indirectly through the level of income and the freedom of the press

Self-Consistent Screening Approximation for Flexible Membranes: Application to Graphene

Crystalline membranes at finite temperatures have an anomalous behavior of the bending rigidity that makes them more rigid in the long wavelength limit. This issue is particularly relevant for applications of graphene in nano- and micro-electromechanical systems. We calculate numerically the height-height correlation function $G(q)$ of crystalline two-dimensional membranes, determining the renormalized bending rigidity, in the range of wavevectors $q$ from $10^{-7}$ \AA$^{-1}$ till 10 \AA$^{-1}$ in the self-consistent screening approximation (SCSA). For parameters appropriate to graphene, the calculated correlation function agrees reasonably with the results of atomistic Monte Carlo simulations for this material within the range of $q$ from $10^{-2}$ \AA$^{-1}$ till 1 \AA$^{-1}$. In the limit $q\rightarrow 0$ our data for the exponent $\eta$ of the renormalized bending rigidity $\kappa_R(q)\propto q^{-\eta}$ is compatible with the previously known analytical results for the SCSA $\eta\simeq 0.82$. However, this limit appears to be reached only for $q<10^{-5}$ \AA$^{-1}$ whereas at intermediate $q$ the behavior of $G(q)$ cannot be described by a single exponent.Comment: 5 pages, 4 figure

Thermodynamics of quantum crystalline membranes

We investigate the thermodynamic properties and the lattice stability of two-dimensional crystalline membranes, such as graphene and related compounds, in the low temperature quantum regime $T\rightarrow0$. A key role is played by the anharmonic coupling between in-plane and out-of plane lattice modes that, in the quantum limit, has very different consequences than in the classical regime. The role of retardation, namely of the frequency dependence, in the effective anharmonic interactions turns out to be crucial in the quantum regime. We identify a crossover temperature, $T^{*}$, between classical and quantum regimes, which is $\sim 70 - 90$ K for graphene. Below $T^{*}$, the heat capacity and thermal expansion coefficient decrease as power laws with decreasing temperature, tending to zero for $T\rightarrow0$ as required by the third law of thermodynamics.Comment: 13 pages, 1 figur