Redox control of light-induced charge separation in a transition metal cluster: photochemistry of a methyl viologen-substituted [Os-3(CO)10(a-diimine)] cluster

Sub)picosecond transient absorption (TA) and time-resolved infrared (TRIR) spectra of the cluster [OS3(CO)(10-) (AcPy-MV)](2+) (the clication AcPy-MV = Acpy-MV2+ = [2-pyridylacetimine-N-(2-(1'-methyl-4,4'-bipyridine-1,1'-diium-1-yl) ethyl)] (PF6)(2)) (1(2+)) reveal that photoinduced electron transfer to the electron-accepting 4,4'-bipyridine-1,1'diium (MV2+) moiety competes with the fast relaxation of the initially populated sigmapi* excited state of the cluster to the ground state and/or cleavage of an Os-Os bond. The TA spectra of cluster 12 in acetone, obtained by irradiation into its lowest-energy absorption band, show the characteristic absorptions of the one-electron-reduced MV*(+) unit at 400 and 615 nm, in accordance with population of a charge-separated (CS) state in which a cluster-core electron has been transferred to the lowest pi* orbital of the remote MV2+ unit. This assignment is confirmed by picosecond TRIR spectra that show a large shift of the pilot highest-frequency nu(CO) band of 1(2+) by ca. +40 cm(-1), reflecting the photooxidation of the cluster core. The CS state is populated via fast (4.2 x 10(11) s(-1)) and efficient (88%) oxidative quenching of the optically populated sigmapi* excited state and decays biexponentially with lifetimes of 38 and 166 ps (1:2:1 ratio) with a complete regeneration of the parent cluster. About 12% of the cluster molecules in the sigmapi* excited state form long-lived open-core biradicals. In strongly coordinating acetonitrile, however, the cluster core-to-MV2+ electron transfer in cluster 12+ results in the irreversible formation of secondary photoproducts with a photooxidized cluster core. The photochemical behavior of the [Os-3(CO)(10)(alpha-diimine-MV)](2+) (donor-acceptor) dyad can be controlled by an externally applied electronic bias. Electrochemical one-electron reduction of the MV2+ moiety prior to the irradiation reduces its electron-accepting character to such an extent that the photoinduced electron transfer to MV*+ is no longer feasible. Instead, the irradiation of reduced cluster 1(.)+ results in the reversible formation of an open-core zwitterion, the ultimate photoproduct also observed upon irradiation of related nonsubstituted clusters [Os-3(CO)(10)(alpha-diimine)] in strongly coordinating solvents such as acetonitrile.

Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

A cluster-based implementation of a fault-tolerant parallel reduction algorithm using swarm-array computing

Recent research in multi-agent systems incorporate fault tolerance concepts. However, the research does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely ‘Intelligent Agents’. In the approach considered a task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The agents hence contribute towards fault tolerance and towards building reliable systems. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

The use of trajectory cluster analysis to interpret trace gas measurements at Mace Head, Ireland

A first step in interpreting the wide variation in trace gas concentrations measured over time at a given site is to classify the data according to the prevailing weather conditions. In order to classify measurements made during two intensive field campaigns at Mace Head, on the west coast of Ireland, an objective method of assigning data to different weather types has been developed. Air-mass back trajectories calculated using winds from ECMWF analyses, arriving at the site in 1995–1997, were allocated to clusters based on a statistical analysis of the latitude, longitude and pressure of the trajectory at 12 h intervals over 5 days. The robustness of the analysis was assessed by using an ensemble of back trajectories calculated for four points around Mace Head. Separate analyses were made for each of the 3 years, and for four 3-month periods. The use of these clusters in classifying ground-based ozone measurements at Mace Head is described, including the need to exclude data which have been influenced by local perturbations to the regional flow pattern, for example, by sea breezes. Even with a limited data set, based on 2 months of intensive field measurements in 1996 and 1997, there are statistically significant differences in ozone concentrations in air from the different clusters. The limitations of this type of analysis for classification and interpretation of ground-based chemistry measurements are discussed.

Multivariable cluster analysis for high-speed industrial machinery

The overall operation and internal complexity of a particular production machinery can be depicted in terms of clusters of multidimensional points which describe the process states, the value in each point dimension representing a measured variable from the machinery. The paper describes a new cluster analysis technique for use with manufacturing processes, to illustrate how machine behaviour can be categorised and how regions of good and poor machine behaviour can be identified. The cluster algorithm presented is the novel mean-tracking algorithm, capable of locating N-dimensional clusters in a large data space in which a considerable amount of noise is present. Implementation of the algorithm on a real-world high-speed machinery application is described, with clusters being formed from machinery data to indicate machinery error regions and error-free regions. This analysis is seen to provide a promising step ahead in the field of multivariable control of manufacturing systems.

A cluster computing implementation of a Monte Carlo simulation of a particle growth mechanism

Clusters of computers can be used together to provide a powerful computing resource. Large Monte Carlo simulations, such as those used to model particle growth, are computationally intensive and take considerable time to execute on conventional workstations. By spreading the work of the simulation across a cluster of computers, the elapsed execution time can be greatly reduced. Thus a user has apparently the performance of a supercomputer by using the spare cycles on other workstations.

Simultaneous observations of reconnection pulses at Cluster and their effects on the cusp aurora observed at the Chinese Yellow River station

While the Cluster spacecraft were located near the high-latitude magnetopause, between 1010 and 1040 UT on 16 January 2004, three typical flux transfer event (FTE) signatures were observed. During this interval, simultaneous and conjugated all‐sky camera measurements, recorded at Yellow River Station, Svalbard, are available at 630.0 and 557.7 nm that show poleward‐moving auroral forms (PMAFs), consistent with magnetic reconnection at the dayside magnetopause. Simultaneous FTEs seen at the magnetopause mainly move northward, but having duskward (eastward) and tailward velocity components, roughly consistent with the observed direction of motion of the PMAFs in all‐sky images. Between the PMAFs meridional keograms, extracted from the all‐sky images, show intervals of lower intensity aurora which migrate equatorward just before the PMAFs intensify. This is strong evidence for an equatorward eroding and poleward moving open‐closed boundary associated with a variable magnetopause reconnection rate under variable IMF conditions. From the durations of the PMAFs, we infer that the evolution time of FTEs is 5–11 minutes from its origin on the magnetopause to its addition to the polar cap.

On merging gradient estimation with mean-tracking techniques for cluster identification

This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.

Neural network basis function center selection using cluster analysis

This paper deals with the selection of centres for radial basis function (RBF) networks. A novel mean-tracking clustering algorithm is described as a way in which centers can be chosen based on a batch of collected data. A direct comparison is made between the mean-tracking algorithm and k-means clustering and it is shown how mean-tracking clustering is significantly better in terms of achieving an RBF network which performs accurate function modelling.

Cluster analysis for multivariable process control

This paper describes the novel use of cluster analysis in the field of industrial process control. The severe multivariable process problems encountered in manufacturing have often led to machine shutdowns, where the need for corrective actions arises in order to resume operation. Production faults which are caused by processes running in less efficient regions may be prevented or diagnosed using a reasoning based on cluster analysis. Indeed the intemal complexity of a production machinery may be depicted in clusters of multidimensional data points which characterise the manufacturing process. The application of a Mean-Tracking cluster algorithm (developed in Reading) to field data acquired from a high-speed machinery will be discussed. The objective of such an application is to illustrate how machine behaviour can be studied, in particular how regions of erroneous and stable running behaviour can be identified.

PINCER trial: a cluster randomised trial comparing the effectiveness and cost-effectiveness of a pharmacist-led IT-based intervention with simple feedback in reducing rates of clinically important errors in medicines management in general practices

Background: Medication errors in general practice are an important source of potentially preventable morbidity and mortality. Building on previous descriptive, qualitative and pilot work, we sought to investigate the effectiveness, cost-effectiveness and likely generalisability of a complex pharm acist-led IT-based intervention aiming to improve prescribing safety in general practice. Objectives: We sought to: • Test the hypothesis that a pharmacist-led IT-based complex intervention using educational outreach and practical support is more effective than simple feedback in reducing the proportion of patients at risk from errors in prescribing and medicines management in general practice. • Conduct an economic evaluation of the cost per error avoided, from the perspective of the National Health Service (NHS). • Analyse data recorded by pharmacists, summarising the proportions of patients judged to be at clinical risk, the actions recommended by pharmacists, and actions completed in the practices. • Explore the views and experiences of healthcare professionals and NHS managers concerning the intervention; investigate potential explanations for the observed effects, and inform decisions on the future roll-out of the pharmacist-led intervention • Examine secular trends in the outcome measures of interest allowing for informal comparison between trial practices and practices that did not participate in the trial contributing to the QRESEARCH database. Methods Two-arm cluster randomised controlled trial of 72 English general practices with embedded economic analysis and longitudinal descriptive and qualitative analysis. Informal comparison of the trial findings with a national descriptive study investigating secular trends undertaken using data from practices contributing to the QRESEARCH database. The main outcomes of interest were prescribing errors and medication monitoring errors at six- and 12-months following the intervention. Results: Participants in the pharmacist intervention arm practices were significantly less likely to have been prescribed a non-selective NSAID without a proton pump inhibitor (PPI) if they had a history of peptic ulcer (OR 0.58, 95%CI 0.38, 0.89), to have been prescribed a beta-blocker if they had asthma (OR 0.73, 95% CI 0.58, 0.91) or (in those aged 75 years and older) to have been prescribed an ACE inhibitor or diuretic without a measurement of urea and electrolytes in the last 15 months (OR 0.51, 95% CI 0.34, 0.78). The economic analysis suggests that the PINCER pharmacist intervention has 95% probability of being cost effective if the decision-maker’s ceiling willingness to pay reaches £75 (6 months) or £85 (12 months) per error avoided. The intervention addressed an issue that was important to professionals and their teams and was delivered in a way that was acceptable to practices with minimum disruption of normal work processes. Comparison of the trial findings with changes seen in QRESEARCH practices indicated that any reductions achieved in the simple feedback arm were likely, in the main, to have been related to secular trends rather than the intervention. Conclusions Compared with simple feedback, the pharmacist-led intervention resulted in reductions in proportions of patients at risk of prescribing and monitoring errors for the primary outcome measures and the composite secondary outcome measures at six-months and (with the exception of the NSAID/peptic ulcer outcome measure) 12-months post-intervention. The intervention is acceptable to pharmacists and practices, and is likely to be seen as costeffective by decision makers.