Data Mining a Medieval Medical Text Reveals Patterns in Ingredient Choice That Reflect Biological Activity against Infectious Agents

We used established methodologies from network science to identify patterns in medicinal ingredient combinations in a key medieval text, the 15th-century Lylye of Medicynes, focusing on recipes for topical treatments for symptoms of microbial infection. We conducted experiments screening the antimicrobial activity of selected ingredients. These experiments revealed interesting examples of ingredients that potentiated or interfered with each other’s activity and that would be useful bases for future, more detailed experiments. Our results highlight (i) the potential to use methodologies from network science to analyze medieval data sets and detect patterns of ingredient combination, (ii) the potential of interdisciplinary collaboration to reveal different aspects of the ethnopharmacology of historical medical texts, and (iii) the potential development of novel therapeutics inspired by premodern remedies in a time of increased need for new antibiotics.The pharmacopeia used by physicians and laypeople in medieval Europe has largely been dismissed as placebo or superstition. While we now recognize that some of the materia medica used by medieval physicians could have had useful biological properties, research in this area is limited by the labor-intensive process of searching and interpreting historical medical texts. Here, we demonstrate the potential power of turning medieval medical texts into contextualized electronic databases amenable to exploration by the use of an algorithm. We used established methodologies from network science to reveal patterns in ingredient selection and usage in a key text, the 15th-century Lylye of Medicynes, focusing on remedies to treat symptoms of microbial infection. In providing a worked example of data-driven textual analysis, we demonstrate the potential of this approach to encourage interdisciplinary collaboration and to shine a new light on the ethnopharmacology of historical medical texts

Synchronization in networks with multiple interaction layers

The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network

Perception of non-financial risk determinants in SMEs in Visegrad countries

Research background: The identification of risks and their management is a key task of strategic management. The right and early identification of risk sources can help companies to survive not only during a crisis period. However, small and medium enterprises (SMEs) underestimate the necessity to analyze risks and implement the enterprise risk management (ERM). Purpose of the article: The primary aim of the contribution is to identify the most important non-financial risks and their causes in the V4 countries and to analyze the perception of these risks by SME owners. Methods: The results me basal on the sup, e conducted in 2018. The valid questionnaire of 1781 owners of SMEs from four countries was evaluated and analyzed to fulfil the main objective. The statistical hypotheses were con-firmed through statistical methods such as Z-score and Chi-square test. The SPSS Statistics was used for data evaluation. Findings & Value added: The results can be interesting not only, tor research organizations investigating the development of SMEs, but also for state institutions or private agencies seeking to adapt national support for SMEs. It was discovered that the entrepreneur's country is the most important factor for the perception of the sources of safety risk, legal risk, and other business risks. There are differences in managers' perception in case of other risk sources (corruption and clientelism) between entrepreneurs from the Czech Republic and other countries of the Visegrad Group. The SMEs' country of origin is an important factor for the evaluation of the source of non-financial risks (safety risk, legal risk and other business risks). Differences in the perception of safe-ty risk sources between entrepreneurs from the Czech Republic and Poland were confirmed. More than 25% of SMEs in the Visegrad Group perceive frequent changes of the legal regulation as a legal risk