A network is a collection of nodes and edges, where an edge connects two nodes. Many
social, natural and engineered systems can be represented as networks. Examples include …

The spontaneous emergence of patterns in nature, such as stripes and spots, can be
mathematically explained by reaction-diffusion systems. These patterns are often referred as …

ABSTRACT A potential issue of interest is figuring out how the combination of temporal and
higher-order interactions influences the collective dynamics of the brain, specifically …

The spontaneous emergence of ordered structures, known as Turing patterns, in complex
networks is a phenomenon that holds potential applications across diverse scientific fields …

Abstract Gierer–Meinhardt (G–M) model is a classical reaction diffusion (RD) model to
describe biological and chemical phenomena. Turing patterns of G–M model in continuous …

In the face of persistent threats posed by infectious diseases, despite remarkable medical
advancements, understanding and efficiently controlling their spatial spread through …

Infectious diseases are a major threat to global health. Spatial patterns revealed by
epidemic models governed by reaction–diffusion systems can serve as a potential trend …

The study of reaction-diffusion systems on networks is of paramount relevance for the
understanding of nonlinear processes in systems where the topology is intrinsically discrete …

Nature is a blossoming of regular structures, signature of self-organization of the underlying
microscopic interacting agents. Turing theory of pattern formation is one of the most studied …

Topological signals are dynamical variables not only defined on nodes but also on links of a
network that are gaining significant attention in non-linear dynamics and topology and have …