A case study in the mechanical verification of fault tolerance

To date, there is little evidence that modular reasoning about fault-tolerant systems can simplify the verification process in practice. This question is studied using a prominent example from the fault tolerance literature: the problem of reliable broadcast in point-to-point networks subject to crash failures of processes. The experiences from this case study show how modular specification techniques and rigorous proof re-use can indeed help in such undertakings.     

Sulfite Action in Glycolytic Inhibition: In Vivo Real‐Time Observation by Hyperpolarized 13C NMR Spectroscopy

Detecting the molecular targets of xenobiotic substances in vivo poses a considerable analytical challenge. Here, we describe the use of an NMR‐based tracer methodology for the instantaneous in vivo observation of sulfur(IV) action on cellular metabolism. Specifically, we find that glycolytic flux is directed towards sulfite adducts of dihydroxyacetone phosphate and pyruvate as off‐pathway intermediates that obstruct glycolytic flux. In particular, the pyruvate–sulfite association hinders the formation of downstream metabolites. The apparent in vivo association constant of pyruvate and sulfite agrees with the apparent inhibition constant of CO₂ formation, thus supporting the importance of pyruvate interception in disturbing central metabolism and inhibiting NAD regeneration.     

Augmented semantic segmentation for the digitization of grinding tools based on deep learning

In order to analyze various process characteristics, grinding simulations can be used, which need accurate models of the tool and the individual grains. For this purpose, grinding tools can be digitized. To identify characteristic grains from a large number of measurements, each individual grain has to be analyzed and separated from the bond manually. Therefore, a deep learning-based methodology was developed to achieve a high segmentation accuracy of the grain boundaries efficiently. Additionally, a data augmentation approach was investigated to limit the data necessary for learning. The model transferability was quantified by analyzing different states of tool wear.     

Silk proteins for biomedical applications: Bioengineering perspectives

Biomaterials of either natural or synthetic origin are used to fabricate implantable devices, as carriers for bioactive molecules or as substrates to facilitate tissue regeneration. For the design of medical devices it is fundamental to use materials characterized by non-immunogenicity, biocompatibility, slow and/or controllable biodegradability, non-toxicity, and structural integrity. The success of biomaterial-derived biodevices tends to be based on the biomimetic architecture of the materials. Recently, proteins from natural precursors that are essentially structural and functional polymers, have gained popularity as biomaterials. The silks produced by silkworms or spiders are of particular interest as versatile protein polymers. These form the basis for diverse biomedical applications that exploit their unique biochemical nature, biocompatibility and high mechanical strength. This review discusses and summarizes the latest advances in the engineering of silk-based biomaterials, focusing specifically on the fabrication of diverse bio-mimetic structures such as films, hydrogels, scaffolds, nanofibers and nanoparticles; their functionalization and potential for biomedical applications.