Oliver López-Corona

It is widely understood that in order to achieve the 2030 agenda we need to implement evidence-based policymaking, but recently It has started to become clear that it is also key to design coherent policies, and for this, we need to incorporate a complexity approach to take into account SDGs interactions. We construct an interaction (Mutual Information) network using data from SDGs progress in most important metropolitan areas in México. We perform a node ranking analysis and compare the results with a theoretical network. We show that empirical and theoretical networks have a different focus, showing that SDG needs at least different policies for urban and rural areas. We also analyzed the effect of individual (ignoring interactions) SDG achievement using a Bayesian Network. We show that in general monolithic SDG policies translate to a higher probability of low progress. We also made some comments related to the current monolithic general focusing on Poverty fighting by the Mexican government in contrast with what available data suggest would be better: Decent Work and Economic Growth but with a Responsible Consumption and Production. Then investing in education and scientific research in order to advance in Industry, Innovation, and Infrastructure, which requires a strong law and justice procuration system that enables peace, justice, and strong institutions.

One of the classic problems in complex systems is the existence and ubiquity of critically, characterized by scale-invariance in frequency space and a balance between emergence (randomness) and self-organization (order). Another universal characteristic of complex systems is their Antigrafility or the capacity of taking advantage from environmental randomness. Inhere we propose a primer hypothesis that both concepts are related and may be understood under an Information Theory framework using Fisher Information as unifying concept. We make some comments about possible connection with Autopoiesis and Contextuality.

The idea of the paper is to think about the result presented in Numberphile (http://www. numberphile.com/) talk (https://www.youtube.com/watch?v=w-I6XTVZXww) where they claim that 1 + 2 + 3 + ..., the Gauss sum, converges to −1/12. In the video they make two strong statements: one that the Grandi’s Series 1 − 1 + 1 − 1 + 1 − 1 + ... tends to 1/2 and the second that as bizarre as the −1/12 result for the Gauss sum might appears, as it is connected to Physics (this result is related with the number of dimensions in String Theory) then it is plausible. In this work we argue that these two statements reflect adhesion to a particular probability narrative and to a particular scientific philosophical posture. We argue that by doing so, these (Gauss and Grandi series) results and String Theory ultimately, might be mathematical correct but they are scientifically (in the Galileo-Newton-Einstein tradition) inconsistent (at least). The philosophical implications of this problem are also discussed, focusing on the role of evidence and scientific demarcation.

A perfect economic storm emerged in M'exico in what was called (mistakenly under our analysis) The December Error (1994) in which Mexico's economy collapsed. In this paper, we show how Theoretical Psychics may help us to understand the under processes for this kind of economic crisis and eventually perhaps to develop an early warning. We specifically analyze monthly historical time series for inflation from January 1969 to November 2018. We found that Fisher information is insensible to inflation growth in the 80's decade but capture quite good The December Error (TDE). Our results show that under Salinas administration Mexican economy was characterized by unstable stability must probably due to hidden risk policies in the form of macro-economy controls that artificially suppress aleatority out of the system making it fragile. And so, we conclude that it was not at all a December error but a sexenal sustained error of fragilization.

Inhere we present a proposal of how to teach complexity using a Problem Based Learning approach under a set of philosophical principles inspired by the pedagogical experience in sustainability Sciences. We described the context in which we put on practise y these ideas that was a graduate course on Complexity and Data Science applied to Ecology.  In part two we present the final work presented by the students as they wrote it and which we believe could be submitted to a journal by its own merits

Inhere we expand the concept of Holobiont to incorporate niche construction theory in order to increase our understanding of the current planetary crisis. By this, we propose a new ontology, the Ecobiont, as the basic evolutionary unit of analysis. We make the case of \textit{Homo Sapiens} organized around modern cities (technobionts) as a different Ecobiont from classical \textit{Homo Sapiens} (i.e. Hunter-gatherers \textit{Homo Sapiens}). We consider that Ecobiont ontology helps to make visible the coupling of \textit{Homo Sapiens} with other biological entities under processes of natural and cultural evolution. Not to see this coupling hidden systemic risks and enhance the probability of catastrophic events. So Ecobiont ontology is necessary to understand and respond to the current planetary crisis.