Places making: participatory construction of scientifi c culture cities

In the framework of the European project Platform of Local Authorities and Communicators Engaged in Science (PLACES), we analyse the articulations between scientifi c communication, public perception of science, processes of citizen participation and apropiation of space, based on a case study of the inhabitants of Teruel city, Autonomous Community of Aragon, Spain. On the interrelationships between these issues, there are a number of contradictions, such as the difference between a high interest for information about science and technology and a low level of recognition and interaction with local institutions involved in those activities, the complex conceptualization of scientifi c space in relation to the “public-private” pair, or an articulation of a claiming civic rethoric and an insuffi cient co-responsibility. We conclude that, in a local context, the dimension of territoriality and, in particular, the identifi cation with the town, is a central mediation for activating citizen participation as part of processes of appropriation of space for setting up cities of scientifi c culture.

Genetic algorithms for local controller network construction

Local Controller Networks (LCNs) provide nonlinear control by interpolating between a set of locally valid, subcontrollers covering the operating range of the plant. Constructing such networks typically requires knowledge of valid local models. This paper describes a new genetic learning approach to the construction of LCNs directly from the dynamic equations of the plant, or from modelling data. The advantage is that a priori knowledge about valid local models is not needed. In addition to allowing simultaneous optimisation of both the controller and validation function parameters, the approach aids transparency by ensuring that each local controller acts independently of the rest at its operating point. It thus is valuable for simultaneous design of the LCNs and identification of the operating regimes of an unknown plant. Application results from a highly nonlinear pH neutralisation process and its associated neural network representation are utilised to illustrate these issues.