Natural Silk Film for Magnesium Protection: Hydrophobic/Hydrophilic Interaction and Self‐Healing Effect

Biodegradable implants are required in order to provide successful treatment of injuries. Temporary magnesium‐based implants with particular properties are needed in cases when it is desirable not only to maintain vital activity, but also to initiate the self‐healing process of damaged bones or tissues as well. Unfortunately, the use of magnesium alloys is limited due to the fast biodegradability of the applied material. The aim of this research is to improve the corrosion resistance of magnesium alloys by sonochemical treatment in silk solution followed by additional layer‐by‐layer deposition of natural silk on the magnesium surface. The sonication process is carried out at a frequency of 20 kHz during 5–10 min, while the duration of the silk layer deposition is 15 min. The corrosion behavior of magnesium substrates modified by natural silk layer‐by‐layer assembly is studied. Magnesium substrates sonochemically treated in silk solution demonstrate three times better corrosion resistance compared to control samples sonochemically treated in water. Additional deposition of a silk layer enhances obtained corrosion resistance by 18 times, resulting in a 54‐fold increase overall.     

Natural Polyphenols Selectively Inhibit β‐Carbonic Anhydrase from the Dandruff‐Producing Fungus Malassezia globosa: Activity and Modeling Studies

Around 50 % of the worldwide population is affected by dandruff, which is triggered by a variety of factors. The yeast Malassezia globosa has been labeled as the most probable causative agent for the onset of dandruff. The β‐carbonic anhydrase (CA) of MgCA was recently validated as an anti‐dandruff target, with its inhibition being responsible for in vivo growth defects in the fungus. As classical CA inhibitors of the sulfonamide type give rise to permeability problems through biological membranes, finding non‐sulfonamide alternatives for MgCA inhibition is of considerable interest in the cosmetic field. We recently screened a large library of human (h) CA inhibitors for MgCA inhibition, including different chemotypes, such as monothiocarbamates, dithiocarbamates, phenols, and benzoxaboroles. Herein, we expanded the research toward new MgCA inhibitors by considering a set of natural polyphenols (including flavones, flavonols, flavanones, flavanols, isoflavones, and depsides) that exhibited MgCA inhibitory activity in the micromolar range, as well as selectivity for the fungal isozyme over off‐target human isoforms. The binding mode of representative derivatives within the MgCA catalytic cleft was investigated by docking studies using a homology‐built model.     

Learning Fuzzy Set Representations of Partial Shapes on Dual Embedding Spaces

Modeling relations between components of 3D objects is essential for many geometry editing tasks. Existing techniques commonly rely on labeled components, which requires substantial annotation effort and limits components to a dictionary of predefined semantic parts. We propose a novel framework based on neural networks that analyzes an uncurated collection of 3D models from the same category and learns two important types of semantic relations among full and partial shapes: complementarity and interchangeability. The former helps to identify which two partial shapes make a complete plausible object, and the latter indicates that interchanging two partial shapes from different objects preserves the object plausibility. Our key idea is to jointly encode both relations by embedding partial shapes as fuzzy sets in dual embedding spaces. We model these two relations as fuzzy set operations performed across the dual embedding spaces, and within each space, respectively. We demonstrate the utility of our method for various retrieval tasks that are commonly needed in geometric modeling interfaces.     

The DiamondCandy LRnLA algorithm: raising efficiency of the 3D cross-stencil schemes

The Journal of Supercomputing - The parallel efficiency is raised by increasing the locality of calculation. With the locally recursive non-locally asynchronous algorithms method, we have...     

Understanding governance,risk and compliance information systems (GRC IS): The experts view

Although Governance, Risk and Compliance (GRC) is an emerging field of study within the information systems (IS) academic community, the concept behind the acronym has to still be demystified and further investigated. The study investigates GRC systems in depth by (a) reviewing the literature on existing GRC studies, and (b) presenting a field study on views about GRC application by professional experts. The aim of this exploratory study is to understand the aspects and the nature of the GRC system following an enterprise systems approach. The result of this study is a framework of particular GRC characteristics that need to be taken into consideration when these systems are put in place. This framework includes specific areas such as: goals and objectives, purpose of the system, key stakeholders, methodology and requirements prior to implementation, critical success factors and problems/barriers. Further discussion about the issues, the concerns and the diverse views on GRC would assist in developing an agenda for the future research on the GRC field.