This study analyzes the importance of fishing as part of the survival strategies of the Mesolithic and Early Neolithic groups of the Danube Iron Gates. It considers the species of fish present in the archaeological record of the Iron Gates sites, ecology, and possible fishing tools and techniques, in order to determine if the quantities caught during favorable seasons could have also insured food reserves for the winter. The author concludes that the presence of large species like sturgeon may be misleading with regard to how intensively these fish were caught, and that besides common species such as carp and catfish, the bulk of the harvest was mainly of smaller species that had fewer chances of being well preserved in the archaeological record.

Pseudorandom number generators (PRNGs) have always been a central research topic in data science, and chaotic dynamical systems are one of the means to obtain scientifically proven data. Chaotic dynamical systems have the property that they have a seemingly unpredictable and random behavior obtained by making use of deterministic laws. The current paper will show how several notions used in the study of chaotic systems—statistical independence, singularity, and observability—can be used together as a suite of test methods for chaotic systems with high potential of being used in the PRNG or cryptography fields. In order to address these topics, we relied on the adaptation of the observability coefficient used in previous papers of the authors, we calculated the singularity areas for the chaotic systems considered, and we evaluated the selected chaotic maps from a statistical independence point of view. By making use of the three notions above, we managed to find strong correlations between the methods proposed, thus supporting the idea that the resulting test procedure is consistent. Future research directions consist of applying the proposed test procedure to other chaotic systems in order to gather more data and formalize the approach in a test suite that can be used by the data scientist when selecting the best chaotic system for a specific use (PRNG, cryptography, etc.).

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People have always tried to understand and tame the nature around them. It is a well-known fact that the sanest and safe approach from a psychological point of view is to focus on the present moment, the here and now. Nevertheless, we keep looking and living in the past or daydreaming and making predictions about what the future will bring. This paper is looking at this topic trying to unify several perspectives, stemming from a very diverse set of disciplines: biology, genetics, economics and cryptography, which are apparently working in parallel to solve the same problem. They all aim to find a theory of everything, one that can make sense out of chaos, light out of darkness and that can accurately predict the future based on present and past events. The current paper is supposed to inspire researchers to ask themselves tough questions, sometimes completely outside of their comfort zone, that can lead to discoveries with a huge positive impact on us all.