Luca Pappalardo, Ed Manley, Vedran Sekara & Laura Alessandretti 
Nature Computational Science volume 3, pages 588–600 (2023)

We provide a brief review of human mobility science and present three key areas where we expect to see substantial advancements. We start from the mind and discuss the need to better understand how spatial cognition shapes mobility patterns. We then move to societies and argue the importance of better understanding new forms of transportation. We conclude by discussing how algorithms shape mobility behavior and provide useful tools for modelers. Finally, we discuss how progress on these research directions may help us address some of the challenges our society faces today.

Read the full article at: www.nature.com

Marina Dubova, Mirta Galesic, Robert L. Goldstone

Cognitive Science 46(12)

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human–machine interaction, group behavior, and community organization, the individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping society tackle major real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other.

Read the full article at: onlinelibrary.wiley.com

Alessandro Scirè & Valerio Annovazzi-Lodi 

Theory in Biosciences volume 142, pages 291–299 (2023)

This work concerns a many-body deterministic model that displays life-like properties such as emergence, complexity, self-organization, self-regulation, excitability and spontaneous compartmentalization. The model portraits the dynamics of an ensemble of locally coupled polar phase oscillators, moving in a two-dimensional space, that under certain conditions exhibit emergent superstructures. Those superstructures are self-organized dynamic networks, resulting from a synchronization process of many units, over length scales much greater than the interaction range. Such networks compartmentalize the two-dimensional space with no a priori constraints, due to the formation of porous transport walls, and represent a highly complex and novel non-linear behavior. The analysis is numerically carried out as a function of a control parameter showing distinct regimes: static pattern formation, dynamic excitable networks formation, intermittency and chaos. A statistical analysis is drawn to determine the control parameter ranges for the various behaviors to appear. The model and the results shown in this work are expected to contribute to the field of artificial life.

Read the full article at: link.springer.com

David Fajardo-Ortiz, Bart Thijs, Wolfgang Glanzel, Karin R. Sipido

The historical research-funding model, based on the curiosity and academic interests of researchers, is giving way to new strategic funding models that seek to meet societal needs. We investigated the impact of this trend on health research funded by the two leading funding bodies worldwide, i.e. the National Institutes of Health (NIH) in the United States, and the framework programs of the European Union (EU). To this end, we performed a quantitative analysis of the content of projects supported through programmatic funding by the EU and NIH, in the period 2008-2014 and 2015-2020. We used machine learning for classification of projects as basic biomedical research, or as more implementation directed clinical therapeutic research, diagnostics research, population research, or policy and management research. In addition, we analyzed funding for major disease areas (cancer, cardio-metabolic and infectious disease). We found that EU collaborative health research projects clearly shifted towards more implementation research. In the US, the recently implemented UM1 program has a similar profile with strong clinical therapeutic research, while other NIH programs remain heavily oriented to basic biomedical research. Funding for cancer research is present across all NIH and EU programs, and in biomedical as well as more implementation directed projects, while infectious diseases is an emerging theme. We conclude that demand for solutions for medical needs leads to expanded funding for implementation- and impact-oriented research. Basic biomedical research remains present in programs driven by scientific initiative and strategies based on excellence, but may be at risk of declining funding opportunities.

Read the full article at: arxiv.org