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    Seasonal temperature variations and energy demand. A panel cointegration analysis for climate change impact assessment

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    Abstract   This paper presents an empirical study of the relationship between residential energy demand and temperature. Unlike previous studies in this field, the data sample has a global coverage and special emphasis is given to the heterogeneous response of different regions and to the contrasting effects on energy demand for cooling and heating purposes. To account for this we distinguish between different regions, seasons, and energy sources. Short- and long-run temperature demand elasticities are estimated. These features make the model results especially valuable in the analysis of climate change impacts as they provide an empirical basis for the study of the impact of climate change on energy demand. To illustrate the potential of the results as a basis for the study of climate change impacts, the estimates are used in a simple exercise that projects changes in energy demand due to temperatures increase in 2085

    Modello matematico di collettore solare a doppia corrente

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    Tecniche e modelli di progettazione di un collettore solare piano a doppia corrente risolvendo i comuni problemi tecnici dei progettist

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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