Learning and teaching with maps.

El rápido crecimiento de mapas en internet, atlas digitales y Sistemas de Información Geográfica (SIG) exige nuevas habilidades, junto con las tradicionales como la localización de lugares utilizando un mapa. Este recurso explica a los niños y a los jóvenes cómo leer, comprender e interpretar los mapas y a los profesores la manera más eficaz de enseñar con los mapas. Presta especial atención a la forma de aprendizaje con este material que puede contribuir al desarrollo cognitivo y a desarrollar habilidades en aritmética. Describe cómo los profesores pueden planificar un programa de estudios y sugiere actividades para los alumnos desde la escuela primaria a la secundaria. Incluye todos los aspectos del uso de mapas, que abarca todas las modalidades, incluidas los globos y atlas. El texto está ampliamente ilustrado con ejemplos, incluyendo los mapas realizados por los propios niños con materiales convencionales, así como programas informáticos. Una característica particular de este recurso es la integración de mapas digitales y convencionales, de internet adecuados a las necesidades de educación primaria y secundaria. Tiene apéndice con web de organizaciones y recursos citados en el texto, bibliografía e índice alfabético.

Reading maps.

Introduce a los estudiantes entre seis y nueve años en los elementos básicos de los mapas y cómo se utilizan. Apoya la enseñanza acerca de los tipos de mapas, lugares y localidades más allá del medio inmediato de los niños. Con esta publicación pueden conocen cómo el globo terráqueo puede caber en un mapa plano, por qué se usan símbolos en los mapas, los puntos cardinales, meridianos y paralelos, latitud y longitud, cómo los cartógrafos dibujan los mapas, las imágenes por satélite y GPS. Incluye actividades.

A Note on the periodic orbits and topological entropy of graph maps

This paper deals with the relationship between the periodic orbits of continuous maps on graphs and the topological entropy of the map. We show that the topological entropy of a graph map can be approximated by the entropy of its periodic orbits

Comparison of NRT based MAPs and preferred MAPs in adult Nucleus CI24 cochlear implant users

Comparison of subjects' preferred MAPs worn in everyday life and MAPs created using electrically evoked compound action potentials using neural response telemetry measures in adult Nucleus CI24 implant users.

Incorporating Legacy Soil pH Databases into Digital Soil Maps

Soil data and reliable soil maps are imperative for environmental management. conservation and policy. Data from historical point surveys, e.g. experiment site data and farmers fields can serve this purpose. However, legacy soil information is not necessarily collected for spatial analysis and mapping such that the data may not have immediately useful geo-references. Methods are required to utilise these historical soil databases so that we can produce quantitative maps of soil propel-ties to assess spatial and temporal trends but also to assess where future sampling is required. This paper discusses two such databases: the Representative Soil Sampling Scheme which has monitored the agricultural soil in England and Wales from 1969 to 2003 (between 400 and 900 bulked soil samples were taken annually from different agricultural fields); and the former State Chemistry Laboratory, Victoria, Australia where between 1973 and 1994 approximately 80,000 soil samples were submitted for analysis by farmers. Previous statistical analyses have been performed using administrative regions (with sharp boundaries) for both databases, which are largely unrelated to natural features. For a more detailed spatial analysis that call be linked to climate and terrain attributes, gradual variation of these soil properties should be described. Geostatistical techniques such as ordinary kriging are suited to this. This paper describes the format of the databases and initial approaches as to how they can be used for digital soil mapping. For this paper we have selected soil pH to illustrate the analyses for both databases.

Conservation strategy maps: a tool to facilitate biodiversity action planning illustrated using the heath fritillary butterfly

1. The UK Biodiversity Action Plan (UKBAP) identifies invertebrate species in danger of national extinction. For many of these species, targets for recovery specify the number of populations that should exist by a specific future date but offer no procedure to plan strategically to achieve the target for any species. 2. Here we describe techniques based upon geographic information systems (GIS) that produce conservation strategy maps (CSM) to assist with achieving recovery targets based on all available and relevant information. 3. The heath fritillary Mellicta athalia is a UKBAP species used here to illustrate the use of CSM. A phase 1 habitat survey was used to identify habitat polygons across the county of Kent, UK. These were systematically filtered using relevant habitat, botanical and autecological data to identify seven types of polygon, including those with extant colonies or in the vicinity of extant colonies, areas managed for conservation but without colonies, and polygons that had the appropriate habitat structure and may therefore be suitable for reintroduction. 4. Five clusters of polygons of interest were found across the study area. The CSM of two of them are illustrated here: the Blean Wood complex, which contains the existing colonies of heath fritillary in Kent, and the Orlestone Forest complex, which offers opportunities for reintroduction. 5. Synthesis and applications. Although the CSM concept is illustrated here for the UK, we suggest that CSM could be part of species conservation programmes throughout the world. CSM are dynamic and should be stored in electronic format, preferably on the world-wide web, so that they can be easily viewed and updated. CSM can be used to illustrate opportunities and to develop strategies with scientists and non-scientists, enabling the engagement of all communities in a conservation programme. CSM for different years can be presented to illustrate the progress of a plan or to provide continuous feedback on how a field scenario develops.

Fast training of self organizing maps for the visual exploration of molecular compounds

Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

Spin spaces and positive decomposition of linear maps on ordered Banach spaces

Spin factors and generalizations are used to revisit positive generation of B(E, F), where E and F are ordered Banach spaces. Interior points of B(E, F)+ are discussed and in many cases it is seen that positive generation of B(E, F) is controlled by spin structure in F when F is a JBW-algebra.