Matjaž Perc

Journal of The Royal Society Interface Volume 17 Issue 164

 

Beauty is subjective, and as such it, of course, cannot be defined in absolute terms. But we all know or feel when something is beautiful to us personally. And in such instances, methods of statistical physics and network science can be used to quantify and to better understand what it is that evokes that pleasant feeling, be it when reading a book or looking at a painting. Indeed, recent large-scale explorations of digital data have lifted the veil on many aspects of our artistic expressions that would remain forever hidden in smaller samples. From the determination of complexity and entropy of art paintings to the creation of the flavour network and the principles of food pairing, fascinating research at the interface of art, physics and network science abounds. We here review the existing literature, focusing in particular on culinary, visual, musical and literary arts. We also touch upon cultural history and culturomics, as well as on the connections between physics and the social sciences in general. The review shows that the synergies between these fields yield highly entertaining results that can often be enjoyed by layman and experts alike. In addition to its wider appeal, the reviewed research also has many applications, ranging from improved recommendation to the detection of plagiarism.

Source: royalsocietypublishing.org

What is the best public policy to counter the health risk from the Coronavirus, COVID-19? This is the question on everyone’s mind.
It is wise to try and learn from the current situation in China, where the rate of COVID-19 infections was extinguished as a result of a lockdown, and Italy, where hospitals are full and doctors have to make life-death decisions about patients because there are not enough beds to treat everyone in need. The mortality fraction of infected people appears to be higher by an order of magnitude when hospitals are overcrowded, so suppressing the rate of new infections serves the important purpose of allowing those in need to be treated.

Source: blogs.scientificamerican.com

Increasingly, says Jones, these zoonotic diseases are linked to environmental change and human behavior. The disruption of pristine forests driven by logging, mining, road building through remote places, rapid urbanization and population growth is bringing people into closer contact with animal species they may never have been near before, she says.
The resulting transmission of disease from wildlife to humans, she says, is now “a hidden cost of human economic development. There are just so many more of us, in every environment. We are going into largely undisturbed places and being exposed more and more. We are creating habitats where viruses are transmitted more easily, and then we are surprised that we have new ones.”

Source: ensia.com

Petter Törnberg and Justus Uitermark

Front. Sustain. Cities

 

Digital platforms are reshaping cities in the twenty-first century, providing not only new ways of seeing and navigating the world, but also new ways of organizing the economy, our cities and social lives. They bring great promises, claiming to facilitate a new “sharing” economy, outside of the exploitation of the market and the inefficiencies of the state. This paper reflects on this promise, and its associated notion of “self-organization,” by situating digital platforms in a longer history of control, discipline and surveillance. Using Foucault, Deleuze, and Bauman, we scrutinize the theoretical and political notion of “self-organization” and unpack its idealistic connotations: To what extent does self-organization actually imply empowerment or freedom? Who is the “self” in “self-organization,” and who is the user on urban digital platforms? Is self-organization necessarily an expression of the interests of the constituent participants? In this way, the paper broadens the analysis of neoliberal governmentalities to reveal the forms of power concealed under the narratives of “sharing” and “self-organization” of the platform era. We find that control is increasingly moving to lower-level strata, operating by setting the context and conditions for self-organization. Thus, the order of things emerge seemingly naturally from the rules of the game. This points to an emerging form of complex control, which has gone beyond the fast and flexible forms of digital control theorized by Deleuze.

Source: www.frontiersin.org

Sergey Mityagin, Carlos Gershenson, and Alexander Boukhanovsky

Complexity Volume 2020 |Article ID 9135024

 

In this paper, we present an approach to drug addiction simulation and forecasting in the medium and long terms in cities having a high population density and a high rate of social communication. Drug addiction forecasting is one of the basic components of the antidrug policy, giving informational and analytic support both at the regional and at the governmental level. However, views on the drug consumption problem vary in different regions, and as a consequence, several approaches to antidrug policy implementation exist. Thereby, notwithstanding the fact that the phenomenology of the population narcotization process is similar in the different regions, approaches to the modeling of drug addiction may also substantially differ for different kinds of antidrug policies. This paper presents a survey of the available antidrug policies and the corresponding approaches to the simulation of population narcotization. This article considers the approach to the construction of the regression model of anesthesia on the main components formed on the basis of indicators of social and economic development. The substantiation of the chosen method is given, which is associated with a significant correlation of indicators, which characterizes the presence of a small number of superfactors. This allows us to form a conclusion about the general level of development of the region as the main factor determining the drug addiction. A new model is proposed for one of the most widespread antidrug policies, namely, the drug use reduction policy. The model helps determine the significant factors of population narcotization and allows to estimate its damage. The model is tested successfully using St. Petersburg data.

Source: www.hindawi.com