Producción de cerámicas y organización doméstica en las comunidades del Bronce final: procesos de modelado y distribución espacial de los recipientes cerámicos de Genó (noreste de la península ibérica)

This paper focuses on the reconstruction of forming processes and ways of doing of the Late Bronze Age ceramic productions from the settlement of Genó (Lleida, Spain). An integrated analysis of pottery forming with the typological traits of the ceramic ware and the spatial distribution of the technological data between the houses of this site is proposed. The analysis of manufacturing traces revealed that up to eight hand-made forming processes were used to produce the ceramic wares of several houses of the village. Comparison of typological features with pot-forming processes, as well as their spatial distribution, suggest that the production was carried out by several producers or even several groups of producers. Instead, other work processes of forming were probably shared within the context of ceramic production. Furthermore, certain ways of doing prevail over others located at specific houses or sectors of the settlement. This raises new hypotheses about the social interactions and the household organisation of the communities that inhabited the village of Genó during the Late Bronze Age.Este trabajo reconstruye los procesos de modelado y las maneras de hacer de las producciones cerámicas del Bronce final del asentamiento de Genó (Lleida, España). Integra el estudio de los procesos tecnológicos con la tipología de los recipientes y con su distribución entre las casas de este asentamiento. Las trazas de fabricación revelan que se usaron hasta ocho procesos de modelado a mano para producir las vajillas cerámicas de varias viviendas de este poblado. La comparación de la distribución espacial de los recipientes, de sus características tipológicas y sus procesos de modelado sugieren que la producción cerámica estaba a cargo de varios productores o incluso de varios grupos de productores. En cambio, otros procesos de trabajo en el modelado eran probablemente compartidos en el contexto de la fabricación cerámica. Unas maneras de hacer, además, prevalecen sobre otras localizadas en determinadas casas o áreas del asentamiento. Ello permite proponer nuevas hipótesis acerca de las interacciones sociales y la organización doméstica de las comunidades que habitaron el poblado de Genó durante el Bronce final

Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area

Evapotranspiration monitoring allows us to assess the environmental stress on forest and agricultural ecosystems. Nowadays, Remote Sensing and Geographical Information Systems (GIS) are the main techniques used for calculating evapotranspiration at catchment and regional scales. In this study we present a methodology, based on the energy balance equation (B-method), that combines remote sensing imagery with GIS-based climate modelling to estimate daily evapotranspiration (ETd) for several dates between 2003 and 2005. The three main variables needed to compute ETd were obtained as follows: (i) Land surface temperature by means of the Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means of multiple regression analysis and spatial interpolation from meteorological ground stations data at satellite pass, and (iii) net radiation by means of the radiative balance. We calculated ETd using remote sensing data at different spatial and temporal scales (Landsat-7 ETM+, Landsat-5 TM and TERRA/AQUA MODIS, with a spatial resolution of 60, 120 and 1000 m, respectively) and combining three different approaches to calculate the B parameter, which represents an average bulk conductance for the daily-integrated sensible heat flux. We then compared these estimates with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean mountain area. This procedure allowed us to better understand the limitations of ETd modelling and how it needs to be improved, especially in heterogeneous forest areas. The method using Landsat data resulted in a good agreement, R2 test of 0.89, with a mean RMSE value of about 0.6 mm day−1 and an estimation error of ±30 %. The poor agreement obtained using TERRA/AQUA MODIS, with a mean RMSE value of 1.8 and 2.4 mm day−1 and an estimation error of about ±57 and 50 %, respectively. This reveals that ETd retrieval from coarse resolution remote sensing data is troublesome in these heterogeneous areas, and therefore further research is necessary on this issue. Finally, implementing regional GIS-based climate models as inputs in ETd retrieval have has provided good results, making possible to compute ETd at regional scales

Anàlisi de l'adherència a les guies de pràctica clínica i de la qualitat dels documents assistencials a la Síndrome Coronària Aguda Sense Elevació del Segment ST a l'Hospital de Sant Pau

El nivell d'acompliment de les recomanacions de les GPC de la ESC (European Society of Cardiology) per la SCASEST a l'Hospital de Sant Pau als mesos d'octubre a desembre del 2010 és subòptim, similar al d'altres centres americans i europeus, i roman invariable respecte les dades de 2006-2007. El servei de Cardiologia destaca en les recomanacions d'hàbits i control de factors de risc cardiovascular. Existeixen diferències poc rellevants entre els serveis de Cardiologia i Medicina Interna en les recomanacions farmacològiques. No s'ha objectivat una relació significativa entre la qualitat de la informació dels documents assistencials i l'adherència a les GPC

New electrocardiographic criteria to differentiate acute pericarditis and myocardial infarction

Objective Transmural myocardial ischemia induces changes in QRS complex and QT interval duration but, theoretically, these changes might not occur in acute pericarditis provided that the injury is not transmural. This study aims to assess whether QRS and QT duration permit distinguishing acute pericarditis and acute transmural myocardial ischemia. Methods Clinical records and 12-lead electrocardiogram (ECG) at ×2 magnification were analyzed in 79 patients with acute pericarditis and in 71 with acute ST-segment elevation myocardial infarction (STEMI). Results ECG leads with maximal ST-segment elevation showed longer QRS complex and shorter QT interval than leads with isoelectric ST segment in patients with STEMI (QRS: 85.9 ± 13.6 ms vs 81.3 ± 10.4 ms, P = .01; QT: 364.4 ± 38.6 vs 370.9 ± 37.0 ms, P = .04), but not in patients with pericarditis (QRS: 81.5 ± 12.5 ms vs 81.0 ± 7.9 ms, P = .69; QT: 347.9 ± 32.4 vs 347.3 ± 35.1 ms, P = .83). QT interval dispersion among the 12-ECG leads was greater in STEMI than in patients with pericarditis (69.8 ± 20.8 ms vs 50.6 ± 20.2 ms, P <.001). The diagnostic yield of classical ECG criteria (PR deviation and J point level in lead aVR and the number of leads with ST-segment elevation, ST-segment depression, and PR-segment depression) increased significantly (P = .012) when the QRS and QT changes were added to the diagnostic algorithm. Conclusions Patients with acute STEMI, but not those with acute pericarditis, show prolongation of QRS complex and shortening of QT interval in ECG leads with ST-segment elevation. These new findings may improve the differential diagnostic yield of the classical ECG criteria

Modeling air temperature through a combination of remote sensing and GIS data

Air temperature is involved in many environmental processes such as actual and potential evapotranspiration, net radiation and species distribution. Ground meteorological stations provide important local data of air temperature, but a continuous surface for large and heterogeneous areas is also needed. In this paper we present a hybrid methodology between Remote Sensing and Geographical Information Systems to retrieve daily instantaneous, mean, maximum and minimum air temperatures (2002-2004) as well as monthly and annual mean, maximum and minimum air temperatures (2000-2005) on a regional scale (Catalonia, northeast of the Iberian Peninsula) by means of multiple regression analysis and spatial interpolation techniques. To perform multiple regression analysis we have used geographical and multiresolution remotely sensed variables as predictors. The geographical variables we have included are altitude, latitude, continentality and solar radiation. As remote sensing predictors, we have selected those variables that are most closely related with air temperature such as albedo, land surface temperature (LST) and NDVI obtained from Landsat-5 (TM), Landsat-7 (ETM+), NOAA (AVHRR) and TERRA (MODIS) satellites. The best air temperature models are obtained when remote sensing variables are combined with geographical variables: averaged R2 = 0.60 and averaged root mean square error (RMSE) = 1.75C for daily temperatures, and averaged R2 = 0.86 and averaged RMSE = 1.00C for monthly and annual temperatures. The results also show that combined models appear in a higher frequency than only geographical or only remote sensing models (87%, 11% and 2% respectively) and that LST and NDVI are the most powerful remote sensing predictors in air temperature modeling