Oxford reading tree. Teacher's guide 3 : owls and magpies : stages 6-9.

Da explicaciones detalladas para ayudar a los niños a aprender a leer en las primeras etapas. Facilita al profesor una serie de estrategias para la enseñanza de la lectura y una amplia variedad de recursos y materiales de apoyo linguístico. Contiene actividades de apoyo a una serie de estrategiás de lectura, recursos fotocopiables, actividades transversales de los contenidos curriculares, evaluación con hojas de registro. También incluye material adicional.

Oxford reading tree. Teacher's guide 2 : stages 4-5.

Explicaciones detalladas de cómo sacar el máximo provecho de cada etapa. Las ideas y sugerencias de esta guía mantienen y amplían la filosofía de la lectura, y el programa, según la propuesta de métodos de enseñanza establecidos en la guía del primer nivel, que ayudarán a dar a los niños la confianza, y las habilidades necesarias para hacer frente a historias con textos más extensos y complejos. Contiene actividades de apoyo a una serie de estrategias de lectura, recursos fotocopiables, actividades tranversales de los contenidos curriculares, evaluación con hojas de registro. También incluye material adicional.

Oxford reading tree. Teacher's guide 1 : stages 1-3.

Explicaciones detalladas para ayudar a los niños a aprender a leer en las primeras etapas. Facilita al profesor una serie de estrategias para la enseñanza de la lectura y una amplia variedad de recursos y materiales de apoyo lingüístico. Contiene actividades de apoyo a una serie de estrategias de lectura, recursos fotocopiables, actividades transversales de los contenidos curriculares, evaluación con hojas de registro. También incluye material adicional.

Cluster A maladaptive personality patterns in a non-clinical adolescent population

Resumen tomado de la publicación

Cómo aplicar un cluster jerárquico en SPSS

Resumen basado en el de la publicación

Irrigation performance and gross water productivity in furrow-irrigated ornamental tree production

In the ornamental plant production region of Girona (Spain), which is one of the largest of its kind in southern Europe, most of the surface is irrigated using wide blocked-end furrows. The objectives of this paper were: (1) to evaluate the irrigation scheduling methods used by ornamental plant producers; (2) to analyse different scenarios in order to assess how they affect irrigation performance; (3) to evaluate the risk of deep percolation; and (4) to calculate gross water productivity. A two-year study in a representative commercial field, planted with Prunus cerasifera ‘Nigra’, was carried out. The irrigation dose applied by the farmers was slightly smaller than the required water dose estimated by the use of two different methods: the first based on soil water content, and the second based on evapotranspiration. Distribution uniformity and application efficiency were high, with mean values above 87%. Soil water content measurements revealed that even at the end of the furrow, where the infiltrated water depth was greatest, more than 90% of the infiltrated water was retained in the shallowest 40 cm of the soil; accordingly, the risk of water loss due to deep percolation was minimal. Gross water productivity for ornamental tree production was € 11.70 m–3, approximately 20 times higher than that obtained with maize in the same region

Estrategias empresariales para afrontar la competencia internacional: el caso del cluster de confecciones de la industria textil de Atuntaqui

El comercio mundial tiene múltiples actores que está sumamente bien posicionados y otros que buscan nuevas estrategias para mejorar su posicionamiento. Asimismo, las diferencias entre los mercados internacionales, nacionales y/o locales son notables, mientras los unos se expanden a pasos agigantados, los otros lo hacen paso a paso. Por lo tanto, el presente trabajo tiene como objetivo fundamental determinar las estrategias que las empresas del sector de las confecciones del cluster textil de Atuntaqui pueden implementar para hacer frente a la competencia internacional. Con esta referencia, el trabajo se ha dividido en tres capítulos. El primer capítulo, está conformado por un análisis de los principales elementos conceptuales (cadena global de valor, managment dentro de la CGV y cluster industriales); seguido, se presenta un breve recuento de la industria, el comercio mundial y los principales importadores y exportadores. Luego, se analiza las tendencias globales utilizadas por los países de América Latina y el Caribe, entre los que están: plataforma de exportación, clusters y logística internacional. En el segundo capítulo, se analizan las principales estadísticas sobre el comportamiento histórico de las importaciones y exportaciones, la caracterización de las empresas, el ámbito tecnológico, los costos y gastos en los que se ha incurrido en algunos cantones y sobre el mercado laboral. Para finalizar, el tercer capítulo, cuenta con una perspectiva local de la industria en Atuntaqui, con temas, como: el “cluster” de la industria, la caracterización de las empresas, el clima de negocios, el diagnostico FODA y las principales estrategias.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.