August 5th, 2023

Complexity of the COVID-19 pandemic in Maringá

While extensive literature exists on the COVID-19 pandemic at regional and national levels, understanding its dynamics and consequences at the […]

June 21st, 2022

The Physics of Cities

The word “physics” can be understood in at least two ways. First, based on the Greek origin of the word, […]

April 29th, 2022

Clustering free-falling paper motion with complexity and entropy

Many simple natural phenomena are characterized by complex motion that appears random at first glance, but that often displays underlying […]

March 21st, 2022

Permutation Jensen-Shannon distance: A versatile and fast symbolic tool for complex time-series analysis

The main motivation of this paper is to introduce the permutation Jensen-Shannon distance, a symbolic tool able to quantify the […]

December 9th, 2021

Population Density and Spreading of COVID-19 in England and Wales

We investigated daily COVID-19 cases and deaths in the 337 lower tier local authority regions in England and Wales to […]

November 15th, 2021

Determining liquid crystal properties with ordinal networks and machine learning

Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of […]

November 1st, 2021

Commuting network effect on urban wealth scaling

Urban scaling theory explains the increasing returns to scale of urban wealth indicators by the per capita increase of human […]

August 6th, 2021

Association between productivity and journal impact across disciplines and career age

The association between productivity and impact of scientific production is a long-standing debate in science that remains controversial and poorly […]

June 7th, 2021

ordpy: A Python package for data analysis with permutation entropy and ordinal network methods

Since Bandt and Pompe’s seminal work, permutation entropy has been used in several applications and is now an essential tool […]

October 3rd, 2019

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 […]