Inhibitor profiling of the Pseudomonas aeruginosa virulence factor LasB using N-alpha mercaptoamide template-based inhibitors

We report on the synthesis and biological evaluation of a focussed library of N-alpha mercaptoamide containing dipeptides as inhibitors of the zinc metallopeptidase Pseudomonas aeruginosa elastase (LasB, EC 3.4.24.26). The aim of the study was to derive an inhibitor profile for LasB with regard to mapping the S´1 binding site of the enzyme. Consequently, a focussed library of 160 members has been synthesised, using standard Fmoc-solid phase methods (on a Rink-amide resin), in which a subset of amino acids including examples of those with basic (Lys, Arg), aromatic (Phe, Trp), large aliphatic (Val, Leu) and acidic (Asp, Glu) side-chains populated the P´2 position of the inhibitor sequence and all 20 natural amino acids were incorporated, in turn, at the P´1 position. The study has revealed a preference for aromatic and/or large aliphatic amino acids at P´1 and a distinct bias against acidic residues at P´2. Ten inhibitor sequences were discovered that exhibited sub to low micromolar Ki values.

Heat capacities of common ionic liquids - Potential applications as thermal fluids?

Ionic liquids generally have wide liquid ranges and negligible vapour pressures; attractive characteristics for use as media for heat transfer and short heat term storage systems. This review of the limited literature available shows that many common ionic liquids have heat capacities, and thus potential thermal energy storage capabilities, that surpass those of commercial hot-oil and synthetic heat transfer fluids and suggests that there is a role for ionic liquids as novel thermal fluids.

Use of culture and molecular analysis to determine the effect of antibiotic treatment on microbial community diversity and abundance during exacerbation in patients with cystic fibrosis

Background: Anaerobic bacteria are increasingly regarded as important in cystic fibrosis (CF) pulmonary infection. The aim of this study was to determine the effect of antibiotic treatment on aerobic and anaerobic microbial community diversity and abundance during exacerbations in patients with CF.

Methods: Sputum was collected at the start and completion of antibiotic treatment of exacerbations and when clinically stable. Bacteria were quantified and identified following culture, and community composition was also examined using culture-independent methods.

Results: Pseudomonas aeruginosa or Burkholderia cepacia complex were detected by culture in 24/26 samples at the start of treatment, 22/26 samples at completion of treatment and 11/13 stable samples. Anaerobic bacteria were detected in all start of treatment and stable samples and in 23/26 completion of treatment samples. Molecular analysis showed greater bacterial diversity within sputum samples than was detected by culture; there was reasonably good agreement between the methods for the presence or absence of aerobic bacteria such as P aeruginosa (kappa=0.74) and B cepacia complex (kappa=0.92), but agreement was poorer for anaerobes. Both methods showed that the composition of the bacterial community varied between patients but remained relatively stable in most individuals despite treatment. Bacterial abundance decreased transiently following treatment, with this effect more evident for aerobes (median decrease in total viable count 2.3 x 10(7) cfu/g, p=0.005) than for anaerobes (median decrease in total viable count 3 x 10(6) cfu/g, p=0.046).

Conclusion: Antibiotic treatment targeted against aerobes had a minimal effect on abundance of anaerobes and community composition, with both culture and molecular detection methods required for comprehensive characterisation of the microbial community in the CF lung. Further studies are required to determine the clinical significance of and optimal treatment for these newly identified bacteria.

Stressed Web Environments as Strategic Games: Risk Profiles and Weltanschauung

We consider the behaviour of a set of services in a stressed web environment where performance patterns may be difficult to predict. In stressed environments the performances of some providers may degrade while the performances of others, with elastic resources, may improve. The allocation of web-based providers to users (brokering) is modelled by a strategic non-cooperative angel-daemon game with risk profiles. A risk profile specifies a bound on the number of unreliable service providers within an environment without identifying the names of these providers. Risk profiles offer a means of analysing the behaviour of broker agents which allocate service providers to users. A Nash equilibrium is a fixed point of such a game in which no user can locally improve their choice of provider – thus, a Nash equilibrium is a viable solution to the provider/user allocation problem. Angel daemon games provide a means of reasoning about stressed environments and offer the possibility of designing brokers using risk profiles and Nash equilibria.

Influence of micro and macro cracks due to sustained loading on chloride-induced corrosion of reinforced concrete beams

Chloride-induced corrosion of steel is one of the most commonly found problems affecting the durability of reinforced concrete structures in both marine environment and where de-icing salt is used in winter. As the significance of micro-cracks on chloride induced corrosion is not well documented, 24 reinforced concrete beams (4 different mixes - one containing Portland cement and another containing 35% ground granulated blastfurnace slag at 0.45 and 0.65 water-binder ratios) were subjected to three levels of sustained lateral loading (0%, 50% and 100% of the load that can induce 0.1 mm wide cracks on the tension surface of beam - F_0.1) in this work. The beams were then subjected to weekly cycles of wetting with 10% NaCl solution for 1 day followed by 6 days of drying at 20 (±1) °C up to an exposure period of 60 weeks. The progress of corrosion of steel was monitored using half-cell potential apparatus and linear polarisation resistance (LPR) test. These results have shown that macro-cracks (at load F_0.1) and micro-cracks (at 50% of F_0.1) greatly accelerated both the initiation and propagation stages of the corrosion of steel in the concrete beams. Lager crack widths for the F_0.1 load cases caused higher corrosion rates initially, but after about 38 weeks of exposure, there was a decrease in the rate of corrosion. However, such trends could not be found in 50% F _0.1 group of beams. The extent of chloride ingress also was influenced by the load level. These findings suggest that the effect of micro-cracking at lower loads are very important for deciding the service life of reinforced concrete structures in chloride exposure environments. © 2014 4th International Conference on the Durability of Concrete Structures.

A floating point CORDIC based SVD processor

An SVD processor system is presented in which each processing element is implemented using a simple CORDIC unit. The internal recursive loop within the CORDIC module is exploited, with pipelining being used to multiplex the two independent micro-rotations onto a single CORDIC processor. This leads to a high performance and efficient hardware architecture. In addition, a novel method for scale factor correction is presented which only need be applied once at the end of the computation. This also reduces the computation time. The net result is an SVD architecture based on a conventional CORDIC approach, which combines high performance with high silicon area efficiency.

Towards Automated Data-Driven Model Creation for Cloud Computing Simulation

The increasing complexity and scale of cloud computing environments due to widespread data centre heterogeneity makes measurement-based evaluations highly difficult to achieve. Therefore the use of simulation tools to support decision making in cloud computing environments to cope with this problem is an increasing trend. However the data required in order to model cloud computing environments with an appropriate degree of accuracy is typically large, very difficult to collect without some form of automation, often not available in a suitable format and a time consuming process if done manually. In this research, an automated method for cloud computing topology definition, data collection and model creation activities is presented, within the context of a suite of tools that have been developed and integrated to support these activities.

Risk-aware Planning in BDI Agents

The ability of an autonomous agent to select rational actions is vital in enabling it to achieve its goals. To do so effectively in a high-stakes setting, the agent must be capable of considering the risk and potential reward of both immediate and future actions. In this paper we provide a novel method for calculating risk alongside utility in online planning algorithms. We integrate such a risk-aware planner with a BDI agent, allowing us to build agents that can set their risk aversion levels dynamically based on their changing beliefs about the environment. To guide the design of a risk-aware agent we propose a number of principles which such an agent should adhere to and show how our proposed framework satisfies these principles. Finally, we evaluate our approach and demonstrate that a dynamically risk-averse agent is capable of achieving a higher success rate than an agent that ignores risk, while obtaining a higher utility than an agent with a static risk attitude.

k-fold Subsampling based Sequential Backward Feature Elimination

We present a new wrapper feature selection algorithm for human detection. This algorithm is a hybrid featureselection approach combining the benefits of filter and wrapper methods. It allows the selection of an optimalfeature vector that well represents the shapes of the subjects in the images. In detail, the proposed featureselection algorithm adopts the k-fold subsampling and sequential backward elimination approach, while thestandard linear support vector machine (SVM) is used as the classifier for human detection. We apply theproposed algorithm to the publicly accessible INRIA and ETH pedestrian full image datasets with the PASCALVOC evaluation criteria. Compared to other state of the arts algorithms, our feature selection based approachcan improve the detection speed of the SVM classifier by over 50% with up to 2% better detection accuracy.Our algorithm also outperforms the equivalent systems introduced in the deformable part model approach witharound 9% improvement in the detection accuracy