Give us back our planet : a unique collection of poetry from children in Spain and the UK.

Los alumnos de centros escolares de toda España y del Reino Unido se han unido para crear esta colección de originales poemas e ilustraciones. Su trabajo pone de manifiesto una profunda preocupación por el futuro de nuestro planeta. Forma parte del proyecto bilingüe iniciado por el British Council de España y el Ministerio de Educación y Ciencia como parte de su proyecto bilingüe en escuelas estatales.

Writting simple poems : pattern poetry for language acquisition.

Muestra a los profesores cómo pueden utilizar escribir poesía para enseñar y reforzar el vocabulario, la estructura y las partes de la oración, la puntuación, así como otras reglas de la gramática y la escritura. Para cualquier edad o nivel de fluidez, puede ser utilizado como lengua extranjera, o para maestros bilingües como un complemento a su programa de escritura. La primera parte del libro se centra en la metodología y ofrece sugerencias para la forma de integrar la poesía escrita con el plan de estudios. La segunda parte del libro contiene veinticinco modelos de poemas y muestras de poesía escritos por estudiantes de diversos idiomas y edades. La tercera parte del libro ofrece un índice y un glosario de términos gramaticales.

Opening eyes : a poetry collection.

Antología poética que abarca diferentes culturas y siglos, y que incluye una amplia gama de estilos poéticos, empleados por célebres y menos conocidos poetas. Los poemas se agrupan en cinco secciones temáticas. Cada sección concluye con una serie de ejercicios para ayudar a explorar las ideas y el uso del lenguaje de los poetas. Al final de cada sección hay actividades que proporcionan oportunidades para comparar dos o más textos. La colección incluye, entre otros, poemas de William Blake, Eiléan Ni Chuilleanáin, A.E. Housman, Philip Larkin, Jean Sprackland, Rabindranath Tagore, Han Yong-Un, Benjamín Zephaniah. Hay notas sobre los autores .

Songs of ourselves : the University of Cambridge International Examinations anthology of poetry in english.

Antología de poesías pertenecientes a cien poetas de todo el mundo de habla inglesa. Es una introducción a una gran variedad de formas, estilos y contenidos de versos de los últimos cuatro siglos, desde el siglo XVI hasta la actualidad. Su contenido se adapta al estudio del CIE, IGCSE y al programa de estudios del nivel AS y nivel avanzado de literatura en inglés.

GCSE AQA English literature : poetry and anthology.

Libro de texto para estudiantes de enseñanza secundaria de segundo ciclo que estén preparando el examen GCSE (General Certificate of Secondary Education) en el área de Literatura Inglesa según la especificación de AQA (Assessment and Qualifications Alliance). Está estructurado en tres secciones (leer poesía, antología poética, y cuentos) divididas en lecciones que incluyen los objetivos a alcanzar, ejercicios, un resumen con los temas clave, biografías o información contextual sobre determinados escritores o textos, definiciones de los términos literarios más importantes, comentarios de examinadores, y referencias a recursos en línea con materiales adicionales.

Między językiem a światem. O poezji Krystyny Miłobędzkiej

Wydział Filologii Polskiej i Klasycznej: Instytut Filologii Polskiej

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.