El Niño reconstructions and confirmation of a pan-Californian model via Radiolarian evidence

Radiolarian number and/or flux rates extracted from Holocene and fossil sediments are used to help detect the presence of, type of (weak or strong), and exact location of the depocenter under an El Niño. These data, along with known provenances of certain radiolarians, support an earlier model that suggests a weak El Niño is a northern and coupled expression of a more southerly strong component dominated by eastern tropical Pacific water underlain by California current and gyre water.

Confirmation of Data Mining Based Predictions of Protein Function

King, R. D. and Wise, P. H. and Clare, A. (2004) Confirmation of Data Mining Based Predictions of Protein Function. Bioinformatics 20(7), 1110-1118

Using Warp to Control Network Contention in Mermera

Parallel computing on a network of workstations can saturate the communication network, leading to excessive message delays and consequently poor application performance. We examine empirically the consequences of integrating a flow control protocol, called Warp control [Par93], into Mermera, a software shared memory system that supports parallel computing on distributed systems [HS93]. For an asynchronous iterative program that solves a system of linear equations, our measurements show that Warp succeeds in stabilizing the network's behavior even under high levels of contention. As a result, the application achieves a higher effective communication throughput, and a reduced completion time. In some cases, however, Warp control does not achieve the performance attainable by fixed size buffering when using a statically optimal buffer size. Our use of Warp to regulate the allocation of network bandwidth emphasizes the possibility for integrating it with the allocation of other resources, such as CPU cycles and disk bandwidth, so as to optimize overall system throughput, and enable fully-shared execution of parallel programs.

Identifying sources of global contention in constraint satisfaction search

Much work has been done on learning from failure in search to boost solving of combinatorial problems, such as clause-learning and clause-weighting in boolean satisfiability (SAT), nogood and explanation-based learning, and constraint weighting in constraint satisfaction problems (CSPs). Many of the top solvers in SAT use clause learning to good effect. A similar approach (nogood learning) has not had as large an impact in CSPs. Constraint weighting is a less fine-grained approach where the information learnt gives an approximation as to which variables may be the sources of greatest contention. In this work we present two methods for learning from search using restarts, in order to identify these critical variables prior to solving. Both methods are based on the conflict-directed heuristic (weighted-degree heuristic) introduced by Boussemart et al. and are aimed at producing a better-informed version of the heuristic by gathering information through restarting and probing of the search space prior to solving, while minimizing the overhead of these restarts. We further examine the impact of different sampling strategies and different measurements of contention, and assess different restarting strategies for the heuristic. Finally, two applications for constraint weighting are considered in detail: dynamic constraint satisfaction problems and unary resource scheduling problems.

Total synthesis of cyanolide A and confirmation of its absolute configuration.

The tandem allylic oxidation/oxa-Michael reaction promoted by the gem-disubstituent effect and the 2-methyl-6-nitrobenzoic anhydride (MNBA)-mediated dimerization were explored for the efficient and facile synthesis of cyanolide A.

A k-round Elimination Contention Scheme for WLANs

currently in press. This is the first published attempt to engineer QoS into a contention-based MAC layer protocol. The work was based on a cross-layer approach to providing programmability into wireless LANs. The work arose from an EPSRC grant in the "programmable networks" call, with Philips / STM research in Italy (Dr Melpignano). Subsequent follow-on includes the formation of a spin-out company (TOM) based on the idea.