Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-Class Classification with a Convolutional Neural Network

Complex Network Analysis of Mass Violation, Specifically Mass Killing

News reports in media contain news about society’s social and political conditions. With the help of publicly available digital datasets of events, it is possible to study a complex network of mass violations, i.e., Mass Killings. Multiple approaches have been applied to bring essential insights into the events and involved actors. Power law distribution behavior finds in the tail of actor mention, co-actor mention, and actor degree tells us about the dominant behavior of influential actors that grows their network with time. The United States, France, Israel, and a few other countries have been identified as major players in the propagation of Mass Killing throughout the past 20 years. It is demonstrated that targeting the removal of influential actors may stop the spreading of such conflicting events and help policymakers and organizations. This paper aims to identify and formulate the conflicts with the actor’s perspective at a global level for a period of time. This process is a generalization to be applied to any level of news, i.e., it is not restricted to only the global level.

Paving New Roads Towards Biodiversity-Based Drug Development in Brazil: Lessons from the Past and Future Perspectives

Although Brazil gathers two fundamental features to occupy a leading position on the development of biodiversity-based medicines, the largest flora on earth and a broad tradition on the use of medicinal plants, the number of products derived from the national genetic heritage is so far modest, either as single drugs or as herbal medicines. This article highlights some aspects that may have contributed to the low rates of success and proposes new insights for innovation. We initially approach the use of medicinal plants in Brazil, molded by its ethnic diversity, and the development of the local pharmaceutical industry. A discussion of some governmental initiatives to support plant-based drug development is then presented. Employing the economic concept of “middle-income trap,” we further propose that Brazil is stuck in a “middle-level science trap,” since the increase in the number of scientific publications that launched the country to an intermediate publishing position has not been translated into drug development. Two new approaches to escape from this trap are presented, which may result in innovative drug development. The first is based on the exploitation of the antifragility properties of herbal products aiming to investigate non-canonical pharmacodynamics mechanisms of action, aligned with the concepts of system biology. The second is the manufacture of herbal products based on the circular economy principles, including the use of byproducts for the development of new therapeutical agents. The adoption of these strategies may result in innovative phytomedicines, with global competitiveness.

Towards an engineering theory of evolution

Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have an engineering theory of evolution, we will neither be able to meet evolution's potential as an engineering tool, nor understand or limit its unintended consequences for our biological designs. Here, we propose the evotype as a helpful concept for engineering the evolutionary potential of biosystems, or other self-adaptive technologies, potentially beyond the realm of biology.

Thermodynamic optimization subsumed in stability phenomena

In the present paper the possibility of an energetic self-optimization as a consequence of thermodynamic stability is addressed. This feature is analyzed in a low dissipation refrigerator working in an optimized trade-off regime (the so-called Omega function). The relaxation after a perturbation around the stable point indicates that stability is linked to trajectories in which the thermodynamic performance is improved. Furthermore, a limited control over the system is analyzed through consecutive external random perturbations. The statistics over many cycles corroborates the preference for a better thermodynamic performance. Endoreversible and irreversible behaviors play a relevant role in the relaxation trajectories (as well as in the statistical performance of many cycles experiencing random perturbations). A multi-objective optimization reveals that the well-known endoreversible limit works as an attractor of the system evolution coinciding with the Pareto front, which represents the best energetic compromise among efficiency, entropy generation, cooling power, input power and the Omega function. Meanwhile, near the stable state, performance and stability are dominated by an irreversible behavior.