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Learning physical properties of liquid crystals with deep convolutional neural networks

Machine learning algorithms have been available since the 1990s, but it is much more recently that they have come into use also in the physical sciences. While these algorithms have already proven to be useful in uncovering new properties of …

Quenched and Annealed Disorder Mechanisms in Comb-Models with Fractional Operators

Recent experimental findings on anomalous diffusion have demanded novel models that combine annealed (temporal) and quenched (spatial or static) disorder mechanisms. The comb-model is a simplified description of diffusion on percolation clusters, …

Gender difference in candidature processes for Brazilian elections

Researchers of several areas have reported that there are still significant gender differences in their performances within different social systems, as in science and on-line communities, for example. This paper focuses on the gender difference in …

Extensions and Solutions for Nonlinear Diffusion Equations and Random Walks

We investigate a connection between random walks and nonlinear diffusion equations within the framework proposed by Einstein to explain the Brownian motion. We show here how to properly modify such framework in order to handle different physical …

Characterizing stochastic time series with ordinal networks

Approaches for mapping time series to networks have become essential tools for dealing with the increasing challenges of characterizing data from complex systems. Among the different algorithms, the recently proposed ordinal networks stand out due to …

Effects of changing population or density on urban carbon dioxide emissions

The question of whether urbanization contributes to increasing carbon dioxide emissions has been mainly investigated via scaling relationships with population or population density. However, these approaches overlook the correlations between …

Quantifying postural sway dynamics using burstiness and interevent time distributions

We propose an approach for analysing the dynamics of human postural sway using measures applied to study inhomogeneous temporal processes. Basically, we defined zero-crossings of center of pressure (COP) trajectories as events, obtained the sequence …

Anomalous diffusion behavior in parliamentary presence

Concepts of statistical mechanics as well as other typical tools of physics have been largely used in the analysis of several aspects of social systems, for instance, in politics. In this work, we examine parliamentary presence utilizing data from …

Estimating physical properties from liquid crystal textures via machine learning and complexity-entropy methods

Imaging techniques are essential tools for inquiring a number of properties from different materials. Liquid crystals are often investigated via optical and image processing methods. In spite of that, considerably less attention has been paid to the …

Clustering patterns in efficiency and the coming-of-age of the cryptocurrency market

The efficient market hypothesis has far-reaching implications for financial trading and market stability. Whether or not cryptocurrencies are informationally efficient has therefore been the subject of intense recent investigation. Here, we use …