Creating a greater partnership: analysing partnership in the Catholic Church development chain

This paper presents results from a project designed to explore the meaning and function of partnership within the Catholic Church development chain. The geography literature has had little to say about such aid chains, especially those founded on faith-based groups. The relationships between three Catholic Church-based donors - referred to as A, B and C - with development personnel of the diocese of the Abuja Ecclesiastical Province (AEP) as well as other Catholic Church structures in Nigeria were analysed. The aim was to explore the forces behind the relationships and how 'patchy' these relationships were in AEP. Respondents were asked to give each of the donors a score in relation to four questions covering their relationship with the donors. Results suggest that the modus operandi of donor 'A' allows it to be perceived as the 'best' partner, while 'B' was scored less favourably because of a perception that it attempts to act independently of existing structures in Nigeria rather than work through them. There was significant variation between diocese in this regard, as well as between the diocese and other structures of the Church (Provinces, Inter-Provinces and National Secretariat). Thus 'partnership' in the Catholic Church aid chain is a highly complex, contested and 'visioned' term and the development of an analytical framework has to take account of these fundamentals.

Nanospheres on a silver plate

A Viewpoint on: 'Surface Geometry of C60 on Ag(111)' H. I. Li, K. Pussi, K. J. Hanna, L.-L. Wang, D. D. Johnson, H.-P. Cheng, H. Shin, S. Curtarolo, W. Moritz, J. A. Smerdon, R. McGrath, and R. D. Diehl. . Published in Physical Review Letters 103, 056101 (2009) on July 27, 2009.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.