The impact of genome defense on mobile elements in Microbotryum

Repeat induced point mutation (RIP), a mechanism causing hypermutation of repetitive DNA sequences in fungi, has been described as a ‘genome defense’ which functions to inactivate mobile elements and inhibit their deleterious effects on genome stability. Here we address the interactions between RIP and transposable elements in the Microbotryum violaceum species complex. Ten strains of M. violaceum, most of which belong to different species of the fungus, were all found to contain intragenomic populations of copia-like retrotransposons. Intragenomic DNA sequence variation among the copia-like elements was analyzed for evidence of RIP. Among species with RIP, there was no significant correlation between the frequency of RIP-induced mutations and inferred transposition rate based on diversity. Two strains of M. violaceum, from two different plant species but belonging to the same fungal lineage, contained copia-like elements with very low diversity, as would result from a high transposition rate, and these were also unique in showing no evidence of the hypermutation patterns indicative of the RIP genome defense. In this species, evidence of RIP was also absent from a Class II helitron-like transposable element. However, unexpectedly the absolute repetitive element load was lower than in other strains.

Distributed acceleration of mobile radio network optimisation algorithms

The past decade has witnessed explosive growth of mobile subscribers and services. With the purpose of providing better-swifter-cheaper services, radio network optimisation plays a crucial role but faces enormous challenges. The concept of Dynamic Network Optimisation (DNO), therefore, has been introduced to optimally and continuously adjust network configurations, in response to changes in network conditions and traffic. However, the realization of DNO has been seriously hindered by the bottleneck of optimisation speed performance. An advanced distributed parallel solution is presented in this paper, as to bridge the gap by accelerating the sophisticated proprietary network optimisation algorithm, while maintaining the optimisation quality and numerical consistency. The ariesoACP product from Arieso Ltd serves as the main platform for acceleration. This solution has been prototyped, implemented and tested. Real-project based results exhibit a high scalability and substantial acceleration at an average speed-up of 2.5, 4.9 and 6.1 on a distributed 5-core, 9-core and 16-core system, respectively. This significantly outperforms other parallel solutions such as multi-threading. Furthermore, augmented optimisation outcome, alongside high correctness and self-consistency, have also been fulfilled. Overall, this is a breakthrough towards the realization of DNO.

Neural network control of a simple mobile robot

In recent years researchers in the Department of Cybernetics have been developing simple mobile robots capable of exploring their environment on the basis of the information obtained from a few simple sensors. These robots are used as the test bed for exploring various behaviours of single and multiple organisms: the work is inspired by considerations of natural systems. In this paper we concentrate on that part of the work which involves neural networks and related techniques. These neural networks are used both to process the sensor information and to develop the strategy used to control the robot. Here the robots, their sensors, and the neural networks used and all described. 1.

Behaviour and learning in completely autonomous mobile robots

A number of Intelligent Mobile Robots have been developed at the University of Reading. They are completely autonomous in that no umbilical cord attaches to them to extra power supplies or computer station: further, they are not radio controlled. In this paper, the robots are discussed, in their various forms, and the individual behaviours and characteristics which appear are considered.