The success of new scientific areas can be assessed by their potential in contributing to new
theoretical approaches and in applications to real-world problems. Complex networks have …

The AlpArray programme is a multinational, European consortium to advance our
understanding of orogenesis and its relationship to mantle dynamics, plate reorganizations …

We offer a systematic analysis of the use of deep learning networks for stock market analysis
and prediction. Its ability to extract features from a large set of raw data without relying on …

Abstract Globally, 80% of wastewater, among which 28% came from industry, returned to the
ecosystem without treatment or reuse. The discharge of industrial wastewater poses public …

Examining important results and analytical techniques, this graduate-level textbook is a step-
by-step presentation of the structure and function of complex networks. Using a range of …

Using the CAViaR tool to estimate the value-at-risk (VaR) and the Granger causality risk test
to quantify extreme risk spillovers, we propose an extreme risk spillover network for …

Electronic databases, from phone to e-mails logs, currently provide detailed records of
human communication patterns, offering novel avenues to map and explore the structure of …

The local structure of unweighted networks can be characterized by the number of times a
subgraph appears in the network. The clustering coefficient, reflecting the local configuration …

A variety of different social, natural and technological systems can be described by the same
mathematical framework. This holds from the Internet to food webs and to boards of …

We construct a Pearson correlation-based network and a partial correlation-based network,
ie, two minimum spanning trees (MST-Pearson and MST-Partial), to analyze the correlation …