Photovoltaics literature survey (No. 115)

In order to help keep readers up‐to‐date in the field, each issue of Progress in Photovoltaics will contain a list of recently published journal articles that most relevant to its aims and scope. This list is drawn from an extremely wide range of journals, including IEEE Journal of Photovoltaics, Solar Energy Materials and Solar Cells, Renewable Energy, Renewable and Sustainable Energy Reviews, Journal of Applied Physics, and Applied Physics Letters. To assist the reader, the list is separated into broad categories, but please note that these classifications are by no means strict. Also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions please email Ziv Hameiri at ziv.hameiri@unsw.edu.au     

Synthesis and Characterization of Thrombin Conjugated γ‐Fe2O3 Magnetic Nanoparticles for Hemostasis

Thrombin is the final protease produced in the clotting pathways. Thrombin has been used in the clinic more than six decades for topical hemostasis and wound management. In human plasma the half‐life of thrombin is shorter than 15 seconds due to close control by inhibitors. In order to stabilize thrombin, this enzyme was conjugated covalently and physically to γ‐Fe₂O₃ magnetic nanoparticles. The physical conjugation was accomplished through adsorption of thrombin to BSA coating on the nanoparticles. The coagulant activity of the covalently bound thrombin was significantly lower than that of the physically adsorbed thrombin. Leakage of the physically bound thrombin into PBS containing 4% HSA was negligible. The physical conjugation of thrombin onto the nanoparticles stabilized the thrombin against its major inhibitor antithrombin III and improved its storage stability. At optimal CaCl₂ concentration, the clotting time by the bound thrombin is shorter than that of the free enzyme. This novel conjugated thrombin may be an efficient candidate for topical hemostasis and wound healing.     

Automatic boosting of cross-product coverage using Bayesian networks

Closing the feedback loop from coverage data to the stimuli generator is one of the main challenges in the verification process. Typically, verification engineers with deep domain knowledge manually prepare a set of stimuli generation directives for that purpose. Bayesian networks based CDG (coverage directed generation) systems have been successfully used to assist the process by automatically closing this feedback loop. However, constructing these CDG systems requires manual effort and a certain amount of domain knowledge from a machine learning specialist. We propose a new method that boosts coverage in the early stages of the verification process with minimal effort, namely a fully automatic construction of a CDG system that requires no domain knowledge. Experimental results on a real-life cross-product coverage model demonstrate the efficiency of the proposed method.     

Unification Grammars and Off-Line Parsability

Unification grammars are known to be Turing-equivalent; given a grammar G and a word w, it is undecidable whether w L(G). In order to ensure decidability, several constraints on grammars, commonly known as off-line parsability (OLP), were suggested, such that the recognition problem is decidable for grammars which satisfy OLP. An open question is whether it is decidable if a given grammar satisfies OLP. In this paper we investigate various definitions of OLP and discuss their interrelations, proving that some of the OLP variants are indeed undecidable. We then present a novel, decidable OLP constraint which is more liberal than the existing decidable ones.