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

Space-efficient Indexing of Chess Endgame Tables

Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame’s positions is crucial to meeting this objective. This paper updates Heinz’ previous review of approaches to indexing and describes the latest approach by the first and third authors. Heinz’ and Nalimov’s endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov’s EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 10^9 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs.

Space-efficient indexing of endgame tables for chess

Chess endgame tables should provide efficiently the value and depth of any required position during play. The indexing of an endgame’s positions is crucial to meeting this objective. This paper updates Heinz’ previous review of approaches to indexing and describes the latest approach by the first and third authors. Heinz’ and Nalimov’s endgame tables (EGTs) encompass the en passant rule and have the most compact index schemes to date. Nalimov’s EGTs, to the Distance-to-Mate (DTM) metric, require only 30.6 × 109 elements in total for all the 3-to-5-man endgames and are individually more compact than previous tables. His new index scheme has proved itself while generating the tables and in the 1999 World Computer Chess Championship where many of the top programs used the new suite of EGTs.

Influences of space, soil, nematodes and plants on microbial community composition of chalk grassland soils

Microbial communities respond to a variety of environmental factors related to resources (e.g. plant and soil organic matter), habitat (e.g. soil characteristics) and predation (e.g. nematodes, protozoa and viruses). However, the relative contribution of these factors on microbial community composition is poorly understood. Here, we sampled soils from 30 chalk grassland fields located in three different chalk hill ridges of Southern England, using a spatially explicit sampling scheme. We assessed microbial communities via phospholipid fatty acid (PLFA) analyses and PCR-denaturing gradient gel electrophoresis (DGGE) and measured soil characteristics, as well as nematode and plant community composition. The relative influences of space, soil, vegetation and nematodes on soil microorganisms were contrasted using variation partitioning and path analysis. Results indicate that soil characteristics and plant community composition, representing habitat and resources, shape soil microbial community composition, whereas the influence of nematodes, a potential predation factor, appears to be relatively small. Spatial variation in microbial community structure was detected at broad (between fields) and fine (within fields) scales, suggesting that microbial communities exhibit biogeographic patterns at different scales. Although our analysis included several relevant explanatory data sets, a large part of the variation in microbial communities remained unexplained (up to 92% in some analyses). However, in several analyses, significant parts of the variation in microbial community structure could be explained. The results of this study contribute to our understanding of the relative importance of different environmental and spatial factors in driving the composition of soil-borne microbial communities.

Space physics for graduate students: an activities-based approach

The geospace environment is controlled largely by events on the Sun, such as solar flares and coronal mass ejections, which generate significant geomagnetic and upper atmospheric disturbances. The study of this Sun-Earth system, which has become known as space weather, has both intrinsic scientific interest and practical applications. Adverse conditions in space can damage satellites and disrupt communications, navigation, and electric power grids, as well as endanger astronauts. The Center for Integrated Space Weather Modeling (CISM), a Science and Technology Center (STC) funded by the U.S. National Science Foundation (see http://www.bu.edu/cism/), is developing a suite of integrated physics-based computer models that describe the space environment from the Sun to the Earth for use in both research and operations [Hughes and Hudson, 2004, p. 1241]. To further this mission, advanced education and training programs sponsored by CISM encourage students to view space weather as a system that encompasses the Sun, the solar wind, the magnetosphere, and the ionosphere/thermosphere. This holds especially true for participants in the CISM space weather summer school [Simpson, 2004].

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.