Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.

A qualidade da comunicação dos técnicos e auxiliares de ressonância magnética num serviço de radiologia: um programa de intervenção

O presente estudo preliminar teve como finalidade analisar a qualidade da comunicação dos técnicos e auxiliares de ação médica nos exames de Ressonância Magnética, partindo da observação da linguagem verbal e não-verbal. Por analogia com outros domínios, desenvolveu-se um programa de intervenção que incidiu na formação dos técnicos e auxiliares ação médica do Serviço de Radiologia de um hospital público. Recorrendo a uma grelha de observação, avaliou-se o efeito do treino de competências no aumento dos comportamentos adequados durante as Ressonâncias Magnéticas. De uma forma geral, os resultados analisados demonstraram que a formação teve um efeito significativo nos técnicos e nos auxiliares das ressonâncias magnéticas, originando mudanças positivas no local de trabalho, tal como o desenvolvimento de uma relação mais adequada com os doentes que potencie o sucesso do diagnóstico; "Analysis of communication quality of technicians and auxiliaries of MRI radiology service" Abstract: With this preliminary study, we intented to analyze the quality of communication in magnetic resonance imaging exams, starting from the observation of verbal and non-verbal language. By analogy with other areas, it was developed an intervention program focused on the training of technicians and operational assistants of the Radiology service of public hospital. Using a grid note, we assessed the effect of skills training in the increased of appropriate behaviour during the MRIs. In General, the results examined showed that the training had a significant effect on operational assistants and technicians of MRIs, resulting in positive changes in the workplace, such as developing a proper relationship with patients to promote the success of the diagnosis.

Using syntactic and semantic features for classifying mo- dal values in the portuguese language

This paper presents a study made in a field poorly explored in the Portuguese language – modality and its automatic tagging. Our main goal was to find a set of attributes for the creation of automatic tag- gers with improved performance over the bag-of-words (bow) approach. The performance was measured using precision, recall and F1. Because it is a relatively unexplored field, the study covers the creation of the corpus (composed by eleven verbs), the use of a parser to extract syntac- tic and semantic information from the sentences and a machine learning approach to identify modality values. Based on three different sets of attributes – from trigger itself and the trigger’s path (from the parse tree) and context – the system creates a tagger for each verb achiev- ing (in almost every verb) an improvement in F1 when compared to the traditional bow approach.