Lichens are symbiotic organisms with an extraordinary capability to colonise areas of extreme climate and heavily contaminated sites, such as metal-rich habitats. Lichens have developed several mechanisms to overcome the toxicity of metals, including the ability to bind metal cations to extracellular sites of symbiotic partners and to subsequently form oxalates. Calcium is an essential alkaline earth element that is important in various cell processes. Calcium can serve as a metal ligand but can be toxic at elevated concentrations. This study investigated calcium-rich and calcium-poor sites and the lichen species that inhabit them (Cladonia sp.). The calcium content of these lichen species were analyzed, along with localized calcium oxalate formed in thalli collected from each site. The highest concentration of calcium was found in the lichen squamules, which can serve as a final deposit for detoxification. Interestingly, the highest content of calcium in Cladonia furcata was localized to the upper part of the thallus, which is the youngest. The produced calcium oxalates were species-specific. Whewellite (CaC₂O₄∙H₂O) was formed in the case of C. furcata and weddellite (CaC₂O₄∙2H₂O) was identified in C. foliacea.

With the increase in usage of computer systems and computer networks, the problem of intrusion detection in network security has become an important issue. In this paper, we discuss approaches that simplify network administrator’s work. We applied clustering methods for security incident profiling. We considerK-means, PAM, and CLARA clustering algorithms. For this purpose, we used data collected in Warden system from various security tools. We do not aim to differentiate between normal and abnormal network traffic, but we focus on grouping similar threat agents based on attributes of security events. We suggest a case of a fine classification and a case of a coarse classification and discuss advantages of both cases.

At present, there is still no officially accepted and extensively verified implementation of computing the gamma difference distribution allowing unequal shape parameters. We explore four computational ways of the gamma difference distribution with different shape parameters resulting from time series kriging, a forecasting approach based on the best linear unbiased prediction and linear mixed models. The results of our numerical study, with emphasis on using open data science tools, demonstrate that our computational algorithm implemented in high-performance Python(with Numba) is exponentially fast, highly accurate and very reliable. It combines numerical inversion of the characteristic function and the trapezoidal rule with the double exponential oscillatory transformation (DE quadrature). At the double 53-bit precision, our open tool outperformed the speed of the analytical computation based on Tricomi's $U(a,b,z)$ function in CAS software (commercial Mathematica, open SageMath) by 1.5–2 orders. At the default precision of scientific numerical computational tools, it exceeded open SciPy, NumPy and commercial MATLAB 5–10 times. The potential future application of our tool for a mixture of characteristic functions could open new possibilities for fast data analysis based on exact probability distributions in areas like multidimensional statistics, measurement uncertainty analysis in metrology, as well as in financial mathematics, and risk analysis.

In extinct archosaurs, brain proportions have been inferred from the morphology of fossilized endocasts. Here we provide the first neurocranial and paleoneurological description of the basal, small-bodied tyrannosauroid Dilong paradoxus compared with larger tyrannosaurids, like Tyrannosaurus rex. Dilong differs from other tyrannosauroids in the proportions of cerebral and cerebellar regions, morphology of venous sinuses, and superimposed position of the forebrain relative to the rest of the endocast. Whereas endocasts of Tyrannosaurus show a more linear configuration and likely contained within a thick intersticial space, the endocast of Dilong indicates an S-shaped brain protected by thinner meninges. Based on our statistic analysis and comparisons with modern crocodilians, we hypothesize that increased body size likely imposed a new spatial configuration for development of the central nervous system during the evolution of gigantism in tyrannosaurs.

In 2014, physicists and data scientists F. Perez and B. Granger started an ambitious project Jupyter with goals of developing a powerful, universal and open virtual interactive scientific environment. Today, Jupyter is the most widely used technology for performing scientific calculations, open data analysis, processing, and reporting, but it has also become a very important educational tool. Our article summarizes pedagogical and technological aspects and experience from using Jupyter notebooks with SageMath in our research and teaching university courses dealing with main mathematical domains. The ideas will be introduced and reflected in the framework of STEM education with modern active learning approaches together with current visions of the EU strategy for advancing the economy and sustainable growth of the EU.