Moving on. Where should the university map collection be going?

This paper argues for the importance of retaining a map library presence on UK university campuses at a time when many are under threat of closure, and access to geospatial data is increasingly moving to web-based services. It is suggested that the need for local expertise is undiminished and map curators need to redefine themselves as geoinformation specialists, preserving their paper map collections, but also meeting some of the challenges of GIS, and contributing to national developments in the construction of distributed geolibraries and the provision of metadata, especially with regard to local data sets.

Imagining migration: Placing children's understanding of 'moving house' in Malawi and Lesotho

Research pertaining to children's geographies has mainly focused on children's physical experiences of space, with their 'imagined geographies' receiving far less attention. The few studies of children's imagined geographies that exist tend to focus on children's national identities and their understanding of distant places. However, children's lives are not necessarily static and they often move between places. Research has not so far considered children's images of these transitional spaces or how such images are constructed. Through an examination of over 800 thematic drawings and stories, regarding 'moving house, produced by children aged 10-17 years in urban and rural communities of Lesotho and Malawi, this paper explores southern African children's representations of migration. The research considers how ideas of migration are culturally-constructed based on notions of family, home and kinship, particularly in relation to the fluid family structure characteristic of most southern African societies. The results suggest that most children imagine migration as a household rather than an individual process.. rarely including micro -migrations between extended family households in their drawings. Further, children's images of migration are place-rooted in everyday life experiences. Their representations concentrate on the reasons for migration, both negative and positive, which are specifically related to their local social and environmental situations and whether house moves take place locally or over longer distances. The paper concludes by exploring the implications of these conceptualisations of moving house for children's contemporary migration experiences, particularly in light of changing family structures due to the effects of the HIV/AIDS pandernic. (c) 2005 Elsevier Ltd. All rights reserved

Scale-invariant moving finite elements for nonlinear partial differential equations in two dimensions

A scale-invariant moving finite element method is proposed for the adaptive solution of nonlinear partial differential equations. The mesh movement is based on a finite element discretisation of a scale-invariant conservation principle incorporating a monitor function, while the time discretisation of the resulting system of ordinary differential equations is carried out using a scale-invariant time-stepping which yields uniform local accuracy in time. The accuracy and reliability of the algorithm are successfully tested against exact self-similar solutions where available, and otherwise against a state-of-the-art h-refinement scheme for solutions of a two-dimensional porous medium equation problem with a moving boundary. The monitor functions used are the dependent variable and a monitor related to the surface area of the solution manifold. (c) 2005 IMACS. Published by Elsevier B.V. All rights reserved.

Moving boundary value problems for the wave equation

We study certain boundary value problems for the one-dimensional wave equation posed in a time-dependent domain. The approach we propose is based on a general transform method for solving boundary value problems for integrable nonlinear PDE in two variables, that has been applied extensively to the study of linear parabolic and elliptic equations. Here we analyse the wave equation as a simple illustrative example to discuss the particular features of this method in the context of linear hyperbolic PDEs, which have not been studied before in this framework.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

API-CALC 1.0: a computer program for calculating the average probability of identity allowing for substructure, inbreeding and the presence of close relatives

Individual identification via DNA profiling is important in molecular ecology, particularly in the case of noninvasive sampling. A key quantity in determining the number of loci required is the probability of identity (PIave), the probability of observing two copies of any profile in the population. Previously this has been calculated assuming no inbreeding or population structure. Here we introduce formulae that account for these factors, whilst also accounting for relatedness structure in the population. These formulae are implemented in API-CALC 1.0, which calculates PIave for either a specified value, or a range of values, for F-IS and F-ST.