Percolation in the classical blockmodel

Classical blockmodel is known as the simplest among models of networks with community structure. The model can be also seen as an extremely simply example of interconnected networks. For this reason, it is surprising that the percolation transition in the classical blockmodel has not been examined so far, although the phenomenon has been studied in a variety of much more complicated models of interconnected and multiplex networks. In this paper we derive the self-consistent equation for the size the global percolation cluster in the classical blockmodel. We also find the condition for percolation threshold which characterizes the emergence of the giant component. We show that the discussed percolation phenomenon may cause unexpected problems in a simple optimization process of the multilevel network construction. Numerical simulations confirm the correctness of our theoretical derivations.Comment: 7 pages, 6 figure

Dark triad traits, study and power motives among medical students – a cross-sectional study at a German medical faculty

Background: A good physician should be empathic and altruistic, among other qualities. Therefore, the levels of socially undesirable personality traits (Dark Triad) as well as implicit motives of achievement, affiliation and power (Multi-Motive Grid) among medical students as future physicians were analyzed at two different points in their medical training. Methods: This study includes 380 medical students in their first year and 217 in their third year in Germany. All participants completed the Dirty Dozen (DD) and Multi-Motive Grid (MMG) questionnaires at the end of two different classes as paper-and-pencil tests. Relevant differences of the Dark Triad traits between the medical students and reference sample and the two different cohorts, as well as their implicit motives, the associations of Dark Triad traits and MMG components and gender differences of the Dark Triad traits were calculated. Results: There were no significant group differences between year one and year three medical students in narcissism, psychopathy and Machiavellianism (Dark Triad). There were no significant differences between the medical students and reference sample except in psychopathy. Male students scored significantly higher in the Dark Triad traits than female students. In the MMG, first-year students scored significantly higher levels in Fear of Rejection, and lower levels in Hope of Success and Hope of Power than the third-year students. Some associations were found between narcissism and Machiavelliansim with Hope of Success, Hope of Power and Fear of power. Conclusions: Dark Triad traits already appear to exist before the commencement of medical studies. These traits do not differ significantly between the medical students and reference sample; only a few MMG components seem to differ at different stages of their studies. This lack of differences between the medical students and validation cohort indicates that tests based on (undesirable) personality traits are not suitable criteria for the admission selection of medical students

The Influence of Graphene Content on the Antibacterial Properties of Polycaprolactone

This work contains an analysis of the impact of modifying a bioresorbable polymer—polycaprolactone (PCL)—with various additives on its antibacterial properties. To this end, samples of PCL filament containing various content levels of graphene (GNP), 0.5%, 5%, 10%, were obtained using injection molding. Polymer samples without additives were used for comparison. The next step was to assess the antimicrobial impact of the preparations under study against the following microorganisms: Staphylococcus aureus ATCC 25293, Escherichia coli ATCC 25922, Candida albicans ATCC 10231. Effective bactericidal activity of PCL with small amount of GNP, especially against C. albicans and S. aureus was confirmed. A decrease in this property or even multiplication of microorganisms was observed in direct proportion to the graphene content in the samples

Analysis of the antibacterial properties of polycaprolactone modified with graphene, bioglass and zinc-doped bioglass

Purpose: Innovative biomedical filaments for 3D printing in the form of short and biodegradable composite sticks modified with various additives were used to prepare biomaterials for further nasal implants. As the respiratory tract is considered to be potentially exposed to contamination during the implantation procedure there is a need to modify the implant with an antibacterial additives. The purpose of this work was to analyze the effect of biodegradable polymer – polycaprolactone (PCL) modification with various additives on its antibacterial properties. Methods: PCL filament modified with graphene (0.5, 5, 10% wt.), bioglass (0.4% wt.) and zinc-doped bioglass (0.4% wt.) were used to print spatial biomaterials using FDM 3D printer. Pure polymer biomaterials without additives were used as reference samples. The key task was to assess the antimicrobial impact of the prepared biomaterials against the following microorganisms: Staphylococcus aureus ATCC 25293, Escherichia coli ATCC 25922, Candida albicans ATCC 10231. Results: The research results point to a significant antibacterial efficacy of the tested materials against S. aureus and C. albicans, which, however, seems to decrease with increasing graphene content in the filaments. A complete lack of antibacterial efficacy against E. coli was determined. Conclusions: The tested biomaterials have important antibacterial properties, especially against C. albicans. The obtained results showed that biomaterials made of modified filaments can be successfully used in implantology, where a need to create temporary tissue scaffolds occurs.</jats:p