Orotic acid as a useful supramolecular synthon for the fabrication of an OPV based hydrogel: stoichiometry dependent injectable behavior

A facile hydrogelation of a p-pyridylenevinylene derivative (PV) bearing oxyethylene chains in the presence of orotic acid (OA) occurs via various non-covalent interactions. Depending on the PV: OA molar ratio, the hydrogel shows vesicle to either cluster-type aggregate or fiber transformation. Visual color tuning, stimuli-responsiveness and injectable properties of the hydrogel are also observed.

Key challenges for the creation and maintenance of specialist protein resources

As the volume of data relating to proteins increases, researchers rely more and more on the analysis of published data, thus increasing the importance of good access to these data that vary from the supplemental material of individual articles, all the way to major reference databases with professional staff and long-term funding. Specialist protein resources fill an important middle ground, providing interactive web interfaces to their databases for a focused topic or family of proteins, using specialized approaches that are not feasible in the major reference databases. Many are labors of love, run by a single lab with little or no dedicated funding and there are many challenges to building and maintaining them. This perspective arose from a meeting of several specialist protein resources and major reference databases held at the Wellcome Trust Genome Campus (Cambridge, UK) on August 11 and 12, 2014. During this meeting some common key challenges involved in creating and maintaining such resources were discussed, along with various approaches to address them. In laying out these challenges, we aim to inform users about how these issues impact our resources and illustrate ways in which our working together could enhance their accuracy, currency, and overall value. Proteins 2015; 83:1005-1013. (c) 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Aircraft Composite Structure Preventive Maintenance

In this paper, a methodology to reduce composite structure maintenance operational cost using SHM systems is adressed. Based on SHM real-time data, in-service structure lifetime prognostic and remaining useful lifetime (RUL) can be performed. Maintenance timetable can be therefore predicted by optimizing inspection times. A probabilistic ap-proach is combined with phenomenological fatigue damage models for composite mate-rials to perform maintenance cost-effectiveness of composite structure. A Monte Carlo method is used to estimate the probability of failure of composite structures and com-pute the average number of composite structure components to be replaced over the component lifetime. The replacement frequency of a given structure component over the aircraft lifetime is assessed. A first application of aeronautical composite structure maintenance is considered. Two composite models to predict the fatigue life and several laminates have been used. Our study shows that maintenance cost-effectiveness depends on material and fatigue loading applied.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

Towards measuring the impact of information availability on maintenance decisions

Decisions concerning maintenance have become increasingly important and requires a diverse set of information as systems become more complex. The availability of information has an impact on the effectiveness of these decisions, and thus on the performance of the asset. This paper highlights the importance of quantifying the value of information on maintenance decisions and asset performance. In particular, we emphasise the need to focus on measuring value as opposed to cost of maintenance, which is the current practice. In this direction, we propose a measure - Value of Ownership (VOO) - to assess the value of information and performance of maintenance decisions throughout an assets lifecycle. © 2009 IFAC.