The use of process simulation methods in support of organisational learning in availability contracting

Traditional business models in the aerospace industry are based on a conventional supplier to customer relationship based on the design, manufacture and subsequent delivery of the physical product. Service provision, from the manufacturer's perspective, is typically limited to the supply of procedural documentation and the provision of spare parts to the end user as the product passes through the latter stages of its intended lifecycle. Challenging economic and political conditions have resulted in end users re-structuring their core business activities, particularly in the defence sector. This has resulted in the need for original equipment manufacturers (OEMs) to integrate and manage support service activities in partnership with the customer to deliver platform availability. This improves the probability of commercial sustainability for the OEM through shared operational risks while reducing the cost of platform ownership for the customer. The need for OEMs to evolve their design, manufacture and supply strategies by focusing on customer requirements has revealed a need for reconstruction of traditional internal behaviours and design methodologies. Application of organisational learning is now a well recognised principle for innovative companies to achieve long term growth and sustained technical development, and hence, greater market command. It focuses on the process by which the organisation's knowledge and value base changes, leading to improved problem solving ability and capacity for action. From the perspective of availability contracting, knowledge and the processes by which it is generated, used and retained, become primary assets within the learning organisation. This paper will introduce the application of digital methods to asset management by demonstrating how the process of learning can benefit from a digital approach, how product and process design can be integrated within a virtual framework and finally how the approach can be applied in a service context.

Transmetalation reactions with nitrogen-containing

The transmetalation reaction of the aryllithium compound [Li(NCN)](2) (NCN is the monoanionic

Cycloalkenyl Halide Substitution Reactions of Enantiopure Arene cis-Tetrahydrodiols with Boron, Nitrogen and Phosphorus Nucleophiles

Enantiopure arene cis-tetrahydrodiols of bromobenzene and iodobenzene have been obtained in good yields, from chemoselective hydrogenation (rhodium-graphite) of the corresponding cis-dihydrodiol metabolites. Palladium-catalysed substitution of the halogen, by hydrogen, boron, nitrogen and phosphorus nucleophiles, in the acetonide derivatives, has yielded highly functionalised products for application in synthesis with potential as scaffolds for chiral ligands.

The VLT-FLAMES survey of massive stars: Nitrogen abundances for Be-type stars in the Magellanic Clouds

Aims. We compare the predictions of evolutionary models for early-type stars with atmospheric parameters, projected rotational velocities and nitrogen abundances estimated for a sample of Be-type stars. Our targets are located in 4 fields centred on the Large Magellanic Cloud cluster: NGC 2004 and the N 11 region as well as the Small Magellanic Cloud clusters: NGC 330 and NGC 346.

Increasing the accuracy of Nitrogen Dioxide (NO2) pollution mapping using geographically weighted regression (GWR) and geostatistics.

Nitrogen Dioxide (NO2) is known to act as an environmental trigger for many respiratory illnesses. As a pollutant it is difficult to map accurately, as concentrations can vary greatly over small distances. In this study three geostatistical techniques were compared, producing maps of NO2 concentrations in the United Kingdom (UK). The primary data source for each technique was NO2 point data, generated from background automatic monitoring and background diffusion tubes, which are analysed by different laboratories on behalf of local councils and authorities in the UK. The techniques used were simple kriging (SK), ordinary kriging (OK) and simple kriging with a locally varying mean (SKlm). SK and OK make use of the primary variable only. SKlm differs in that it utilises additional data to inform prediction, and hence potentially reduces uncertainty. The secondary data source was Oxides of Nitrogen (NOx) derived from dispersion modelling outputs, at 1km x 1km resolution for the UK. These data were used to define the locally varying mean in SKlm, using two regression approaches: (i) global regression (GR) and (ii) geographically weighted regression (GWR). Based upon summary statistics and cross-validation prediction errors, SKlm using GWR derived local means produced the most accurate predictions. Therefore, using GWR to inform SKlm was beneficial in this study.

Availability of complementary and alternative medicine for people with cancer in the British National Health Service: Results of a national survey

This study assessed access to Complementary and Alternative Medicine (CAM) therapies for people with cancer within the British National Health Service. CAM units were identified through an internet search in 2009. A total of 142 units, providing 62 different therapies, were identified: 105 (74.0%) England; 23 (16.2%) Scotland; 7 (4.9%) each in Wales and Northern Ireland. Most units provide a small number of therapies (median 4, range 1–20), and focus on complementary, rather than alternative approaches. Counselling is the most widely provided therapy (available at 82.4% of identified units), followed by reflexology (62.0%), aromatherapy (59.1%), reiki (43.0%), massage (42.2%). CAM units per million of the population varied between countries (England: 2.2; Wales: 2.3; Scotland: 4.8; Northern Ireland: 5.0), and within countries. Better publicity for CAM units, greater integration of units in conventional cancer treatment centres may help improve access to CAMs.