Risk factors for non compliance using occlusive therapy: a case study

Purpose: compliance with treatment is a common problem when treating amblyopic patients. Visual acuity of amblyopic eye does not improve without effective occlusive therapy. The aim of this study is to identify potential risk factors of non-compliance with treatment when it is implemented by family in amblyopic children. Setting: a quantitative transversal study was performed in a public hospital and in a private clinic in Lisbon.

Assessment of fungal contamination in waste sorting and incineration: case study in Portugal

Organic waste is a rich substrate for microbial growth, and because of that, workers from waste industry are at higher risk of exposure to bioaerosols. This study aimed to assess fungal contamination in two plants handling solid waste management. Air samples from the two plants were collected through an impaction method. Surface samples were also collected by swabbing surfaces of the same indoor sites. All collected samples were incubated at 27◦C for 5 to 7 d. After lab processing and incubation of collected samples, quantitative and qualitative results were obtained with identification of the isolated fungal species. Air samples were also subjected to molecular methods by real-time polymerase chain reaction (RT PCR) using an impinger method to measure DNA of Aspergillus flavus complex and Stachybotrys chartarum. Assessment of particulate matter (PM) was also conducted with portable direct-reading equipment. Particles concentration measurement was performed at five different sizes (PM0.5; PM1; PM2.5; PM5; PM10). With respect to the waste sorting plant, three species more frequently isolated in air and surfaces were A. niger (73.9%; 66.1%), A. fumigatus (16%; 13.8%), and A. flavus (8.7%; 14.2%). In the incineration plant, the most prevalent species detected in air samples were Penicillium sp. (62.9%), A. fumigatus (18%), and A. flavus (6%), while the most frequently isolated in surface samples were Penicillium sp. (57.5%), A. fumigatus (22.3%) and A. niger (12.8%). Stachybotrys chartarum and other toxinogenic strains from A. flavus complex were not detected. The most common PM sizes obtained were the PM10 and PM5 (inhalable fraction). Since waste is the main internal fungal source in the analyzed settings, preventive and protective measures need to be maintained to avoid worker exposure to fungi and their metabolites.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.