Understanding and modeling the mobility of individuals is of paramount importance for public health. In particular, mobility characterization is key to predict the spatial and temporal diffusion of human-transmitted infections. However, the mobility behavior of a person can also reveal relevant information about her/his health conditions. In this paper, we study the impact of people mobility behaviors for predicting the future presence of flu-like and cold symptoms (i.e. fever, sore throat, cough, shortness of breath, headache, muscle pain, malaise, and cold). To this end, we use the mobility traces from mobile phones and the daily self-reported flu-like and cold symptoms of 29 individuals from February 20, 2013 to March 21, 2013. First of all, we demonstrate that daily symptoms of an individual can be predicted by using his/her mobility trace characteristics (e.g. total displacement, radius of gyration, number of unique visited places, etc.). Then, we present and validate models that are able to successfully predict the future presence of symptoms by analyzing the mobility patterns of our individuals. The proposed methodology could have a societal impact opening the way to customized mobile phone applications, which may detect and suggest to the user specific actions in order to prevent disease spreading and minimize the risk of contagion.

 

Are you getting sick? Predicting influenza-like symptoms using human mobility behaviors
Gianni Barlacchi, Christos Perentis, Abhinav Mehrotra, Mirco Musolesi and Bruno Lepri
EPJ Data Science20176:27
https://doi.org/10.1140/epjds/s13688-017-0124-6

Source: epjdatascience.springeropen.com

Empowerment, a concept inspired in part by cybernetics and psychology, describes an agent’s intrinsic motivation to both persist within and operate upon its environment. “Like an organism, it wants to survive. It wants to be able to affect the world,” Salge explained. A Roomba programmed to seek its charging station when its batteries are getting low could be said to have an extremely rudimentary form of empowerment: To continue acting on the world, it must take action to preserve its own survival by maintaining a charge.

Source: www.quantamagazine.org

The aim of this paper is to determine the general preferential attachment function and author fitness, which describe the rich get richer and fit get richer phenomena, in the co-authorship and citation networks of the strategic management scientific community. This has been done by means of the PAFit method using the community’s flagship journal, namely Strategic Management Journal. The results suggest the co-authorship and citation temporal networks are governed by both the fit get richer and the rich get richer processes. The average of the attachment exponents in the co-author network is 0.3 while it is 0.29 in the citation network, which suggests the rich get richer phenomenon is similarly weak in both networks. On the other hand, the distributions of author fitness in both networks have long right tail, which implies that the intrinsic scientific quality of each author plays a crucial role in getting new citations and new co-authorships. Furthermore, author fitness in both co-authorship and citation networks are found to be consistent with the history of the strategic management scientific community.

 

The Rich get Richer and the Fit get Richer Phenomena in Temporal Complex Networks in the Strategic Management Scientific Community
Ronda-Pupo Guillermo Armando, Thong Pham

Source: arxiv.org

Advances in soft robotics will be crucial to the next generation of robot–human interfaces. Soft material systems embed safety at the material level, providing additional safeguards that will expedite their placement alongside humans and other biological systems. However, in order to function in unpredictable, uncontrolled environments alongside biological systems, soft robotic systems should be as robust in their ability to recover from damage as their biological counterparts. There exists a great deal of work on self-healing materials, particularly polymeric and elastomeric materials that can self-heal through a wide variety of tools and techniques. Fortunately, most emerging soft robotic systems are constructed from polymeric or elastomeric materials, so this work can be of immediate benefit to the soft robotics community. Though the field of soft robotics is still nascent as a whole, self-healing and damage resilient systems are beginning to be incorporated into three key support pillars that are enabling the future of soft robotics: actuators, structures, and sensors. This article reviews the state-of-the-art in damage resilience and self-healing materials and devices as applied to these three pillars. This review also discusses future applications for soft robots that incorporate self-healing capabilities.

 

Self-Healing and Damage Resilience for Soft Robotics: A Review

R. Adam Bilodeau & Rebecca K. Kramer

Front. Robot. AI, 03 October 2017 | https://doi.org/10.3389/frobt.2017.00048

Source: www.frontiersin.org

Animal aggregations are visually striking, and as such are popular examples of collective behavior in the natural world. Quantitatively demonstrating the collective nature of such groups, however, remains surprisingly difficult. Inspired by thermodynamics, we applied topological data analysis to laboratory insect swarms and found evidence for emergent, material-like states. We show that the swarms consist of a core “condensed” phase surrounded by a dilute “vapor” phase. These two phases coexist in equilibrium, and maintain their distinct macroscopic properties even though individual insects pass freely between them. We further define a pressure and chemical potential to describe these phases, extending theories of active matter to aggregations of macroscopic animals and laying the groundwork for a thermodynamic description of collective animal groups.

 

Phase Coexistence in Insect Swarms
Michael Sinhuber and Nicholas T. Ouellette
Phys. Rev. Lett. 119, 178003 – Published 24 October 2017

Source: journals.aps.org