Month: August 2021

Science Is Political, and We Must Deal with It

Philip Ball

J. Phys. Chem. Lett. 2021, 12, 27, 6336–6340

The issue is not, then, whether and how science can resist being “politicized”, but how the political and ideological dimensions of science can best be managed to make it most effective and beneficial both as an intellectual quest and as a means of, as Bacon put it, relieving (hu)mankind’s estate.

Read the full article at: pubs.acs.org

Relation between Constitutions, Socioeconomics and The Rule of Law: a quantitative thermodynamic approach

Klaus Jaffe, Edrey Martinez, Ana Cecilia Soarez, Jose Gregorio Contreras, Juan C Correa, Antonio Canova
Based on what we know about thermodynamics of synergy, we explored the relationship between countries socio-cultural order (negentropy), estimated through their constitutions, indicators of Rule of Law and their academic development; with countries indicators of Free Energy (amount of useful work, productivity, socioeconomic health). The analysis of 219 indicators unveiled strong correlations between estimates of the Rule of Law and the number of Academic Publications, with the socioeconomic health indicators: GDP, Human Development Index and Infant Mortality. In contrast, correlations with the length of constitutions (number of words and of articles), suggest that the proliferation of legal rules hinders the rule of law and socioeconomic development, or that under-development and/or the lack of the rule of law foments the proliferation of legal rules. These findings suggest that not any order favors productivity (Free Energy) and that excess regulations and state tutelage increase social entropy decreasing socioeconomic health.

Read the full article at: arxiv.org

A new nature-inspired optimization for community discovery in complex networks

Xiaoyu Li, Chao Gao, Songxin Wang, Zhen Wang, Chen Liu & Xianghua Li 

The European Physical Journal B volume 94, Article number: 137 (2021)

The community structure, owing to its significant status, is of extraordinary significance in comprehending and detecting inherent functions in real networks. However, the community structures are always hard to be identified, and whether the existing algorithms are based on optimization or heuristics, the robustness and accuracy should be improved. The physarum (i.e., slime molds with multi heads) has proved its ability to produce foraging networks. Therefore, we adopt physarum so that the optimization-based community detection algorithms can work more efficiently. Specifically, a physarum-based network model (pnm), which is capable of identifying inter-edges of the community in a network, is used to optimize the prior knowledge of existing evolutional algorithms (i.e., genetic algorithm, particle swarm optimization algorithm and ant colony algorithm). the optimized algorithms have been compared with some advanced methods in synthetic and real networks. experimental results have verified the effectiveness of the proposed method.

Read the full article at: link.springer.com

When less is more: Robot swarms adapt better to changes with constrained communication

Mohamed S. Talamali, Arindam Saha, James A. R. Marshall, and Andreagiovanni Reina
Science Robotics 6(56): eabf1416
https://doi.org/10.1126/scirobotics.abf1416 
video: https://bcove.video/3zwyQpA 

You found a new better bar, with nicer drinks and healthier snacks, but you do not know how to convince your friends to deviate from their established favourite bar and take them to the new better place. Next time, you should consider convincing your friends one by one, rather than reaching out in the group chat. Recent research published today in Science Robotics, suggests that this strategy will increase your probability of convincing the entire group to choose the better bar.
The study has found that a population of naive individuals, when globally connected, can be unable to discard outdated beliefs and adopt better available alternatives. Instead, when the social network is sparse and individuals only share information locally, the population can effectively adapt to changes and reach an agreement in favour of the best option.
Researchers investigated how a swarm of autonomous robots could adapt to environmental changes and found the counterintuitive result that reduced social information would improve the spreading of localised information, and, in turn, allows an informed minority to effectively change the opinion of the entire group. This finding is opposed to the widely accepted and intuitive belief in network science that more connections lead to more effective information exchange. While information spreading speed may indeed increase, the study showed that adaptation—the ability to modify the group’s belief in light of new information—is impaired.

Read the full article at: robotics.sciencemag.org

Atlas of Forecasts: Modeling and Mapping Desirable Futures

Forecasting the future with advanced data models and visualizations.

To envision and create the futures we want, society needs an appropriate understanding of the likely impact of alternative actions. Data models and visualizations offer a way to understand and intelligently manage complex, interlinked systems in science and technology, education, and policymaking. Atlas of Forecasts, from the creator of Atlas of Science and Atlas of Knowledge, shows how we can use data to predict, communicate, and ultimately attain desirable futures.

Using advanced data visualizations to introduce different types of computational models, Atlas of Forecasts demonstrates how models can inform effective decision-making in education, science, technology, and policymaking. The models and maps presented aim to help anyone understand key processes and outcomes of complex systems dynamics, including which human skills are needed in an artificial intelligence–empowered economy; what progress in science and technology is likely to be made; and how policymakers can future-proof regions or nations. This Atlas offers a driver’s seat-perspective for a test-drive of the future.

More at: mitpress.mit.edu