The key role of sufficiency for low demand-based carbon neutrality and energy security across Europe.

A detailed assessment of a low energy demand, 1.5 C compatible pathway is provided for Europe from a bottom-up, country scale modelling perspective. The level of detail enables a clear representation of the potential of sufficiency measures.

Source identification via contact tracing in the presence of asymptomatic patients.

Inferring the source of a diffusion in a large network of agents is a difficult but feasible task, if a few agents act as sensors revealing the time at which they got hit by the diffusion. One of the main limitations of current source identification algorithms is that they assume full knowledge of the contact network, which is rarely the case, especially for epidemics, where the source is called patient zero. Inspired by recent implementations of contact tracing algorithms, we propose a new framework, which we call Source Identification via Contact Tracing Framework (SICTF).

The Energy Return on Investment of Whole-Energy Systems: Application to Belgium.

Planning the defossilization of energy systems while maintaining access to abundant primary energy resources is a non-trivial multi-objective problem encompassing economic, technical, environmental, and social aspects. However, most long-term policies consider the cost of the system as the leading indicator in the energy system models to decrease the carbon footprint. This paper is the first to develop a novel approach by adding a surrogate indicator for the social and economic aspects, the (EROI), in a whole-energy system optimization model.

The effect of transmission variance on observer placement for source-localization.

Detecting where an epidemic started, i.e., which node in a network was the source, is of crucial importance in many contexts.

Locating the source of diffusion in large-scale networks.

How can we localize the source of diffusion in a complex network? Because of the tremendous size of many real networks-such as the internet or the human social graph-it is usually unfeasible to observe the state of all nodes in a network. We show that it is fundamentally possible to estimate the location of the source from measurements collected by sparsely placed observers. We present a strategy that is optimal for arbitrary trees, achieving maximum probability of correct localization.