Políticas e modelos de gestão em unidades de fisioterapia: estratégias para a mudança

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

A Sustenatbilidade empresarial como estratégia na criação de valor

Mestrado em Gestão e Empreendedorismo

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.

Genotoxicity biomarkers in occupational exposure to formaldehyde: the case of histopathology laboratories

Formaldehyde, classified by the IARC as carcinogenic in humans and experimental animals, is a chemical agent that is widely used in histopathology laboratories. The exposure to this substance is epidemiologically linked to cancer and to nuclear changes detected by the cytokinesis-block micronucleus test (CBMN). This method is extensively used in molecular epidemiology, since it provides information on several biomarkers of genotoxicity, such as micronuclei (MN), which are biomarkers of chromosomes breakage or loss, nucleoplasmic bridges (NPB), common biomarkers of chromosome rearrangement, poor repair and/or telomere fusion, and nuclear buds (NBUD), biomarkers of elimination of amplified DNA. The aim of this study is to compare the frequency of genotoxicity biomarkers, provided by the CBMN assay in peripheral lymphocytes and the MN test in buccal cells, between individuals occupationally exposed and non-exposed to formaldehyde and other environmental factors, namely tobacco and alcohol consumption. The sample comprised two groups: 56 individuals occupationally exposed to formaldehyde (cases) and 85 unexposed individuals (controls), from whom both peripheral blood and exfoliated epithelial cells of the oral mucosa were collected in order to measure the genetic endpoints proposed in this study. The mean level of TWA8h was 0.16±0.11ppm (

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: A study case of the 1755 Lisbon tsunami in Algarve, Portugal

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Air contaminants in animal production: the poultry case

A descriptive study was developed in order to assess air contamination caused by fungi and particles in seven poultry units. Twenty seven air samples of 25 litters were collected through impaction method. Air sampling and particle concentration measurement were performed in the pavilions’ interior and also outside premises, since this was the place regarded as reference. Simultaneously, temperature and relative humidity were also registered. Regarding fungal load in the air from the seven poultry farms, the highest value obtained was 24040 CFU/m3 and the lowest was 320 CFU/m3. Twenty eight species/genera of fungi were identified, being Scopulariopsis brevicaulis (39.0%) the most commonly isolated species and Rhizopus sp. (30.0%) the most commonly isolated genus. From the Aspergillus genus, Aspergillus flavus (74.5%) was the most frequently detected species. There was a significant correlation (r=0.487; p=0.014) between temperature and the level of fungal contamination (CFU/m3). Considering contamination caused by particles, in this study, particles with larger dimensions (PM5.0 and PM10) have higher concentrations. There was also a significant correlation between relative humidity and concentration of smaller particles namely, PM0.5 (r=0.438; p=0.025) and PM1.0 (r=0.537; p=0.005). Characterizing typical exposure levels to these contaminants in this specific occupational setting is required to allow a more detailed risk assessment analysis and to set exposure limits to protect workers’ health.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: Astudy case of the 1755 Lisbon tsunami in Algarve, Portugal (vol 182, pg 187, 2010)

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Computing the phase diagram of binary mixtures: A patchy particle case study

We investigate the phase behaviour of 2D mixtures of bi-functional and three-functional patchy particles and 3D mixtures of bi-functional and tetra-functional patchy particles by means of Monte Carlo simulations and Wertheim theory. We start by computing the critical points of the pure systems and then we investigate how the critical parameters change upon lowering the temperature. We extend the successive umbrella sampling method to mixtures to make it possible to extract information about the phase behaviour of the system at a fixed temperature for the whole range of densities and compositions of interest. (C) 2013 AIP Publishing LLC.

Exposure and genotoxicity assessment methodologies: the case of formaldehyde occupational exposure

Formaldehyde (FA) ranks 25th in the overall U.S. chemical production, with more than 5 million tons produced each year. Given its economic importance and widespread use, many people are exposed to FA occupationally. Recently, based on the correlation with nasopharyngeal cancer in humans, the International Agency for Research on Cancer (IARC) confirmed the classification of FA as a Group I substance. Considering the epidemiological evidence of a potential association with leukemia, the IARC has concluded that FA can cause this lymphoproliferative disorder. Our group has developed a method to assess the exposure and genotoxicity effects of FA in two different occupational settings, namely FAbased resins production and pathology and anatomy laboratories. For exposure assessment we applied simultaneously two different techniques of air monitoring: NIOSH Method 2541 and Photo Ionization Detection Equipment with simultaneously video recording. Genotoxicity effects were measured by cytokinesis-blocked micronucleus assay in peripheral blood lymphocytes and by micronucleus test in exfoliated oral cavity epithelial cells, both considered target cells. The two exposure assessment techniques show that in the two occupational settings peak exposures are still occurring. There was a statistical significant increase in the micronucleus mean of epithelial cells and peripheral lymphocytes of exposed individuals compared with controls. In conclusion, the exposure and genotoxicity effects assessment methodologies developed by us allowed to determine that these two occupational settings promote exposure to high peak FA concentrations and an increase in the micronucleus mean of exposed workers. Moreover, the developed techniques showed promising results and could be used to confirm and extend the results obtained by the analytical techniques currently available.

Occupational exposure to particulate matter and fungi in a composting plant: case study in Portugal

The handling of waste can be responsible for occupational exposure to particles and fungi. The aim of this study was to characterize exposure to particles and fungi in a composting plant. Measurements of particulate matter were performed using portable direct-reading equipment. Air samples of 50L were collected through an impaction method with a flow rate of 140L/min onto malt extract agar supplemented with chloramphenicol (0.05%). Surfaces samples were also collected. All the samples were incubated at 27ºC for 5 to 7 days. Particulate matter data showed higher contamination for PM, and PM10 sizes. Aspergillus genus presents the highest air prevalence (90.6%). Aspergillus niger (32.6%), A. fumigatus (26.5%) and A. flavus (16.3%) were the most prevalent fungi in air sampling, and Mucor sp. (39.2%), Aspergillus niger (30.9%) and A. fumigatus (28.7%) were the most found in surfaces. the results obtained claim the attention to the need of further research.

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.

Naturally occurring radioactive materials: a method for assessing the risk of exposure

Naturally Occurring Radioactive Materials (NORM) are materials that are found naturally in the environment and contain radioactive isotopes that can cause negative effects on the health of workers who manipulate them. Present in underground work like mining and tunnel construction in granite zones, these materials are difficult to identify and characterize without appropriate equipment for risk evaluation. The assessing methods were exemplified with a case study applied to the handling and processing of phosphoric rock where one found significant amounts of radioactive isotopes and consequently elevated radon concentrations in enclosed spaces containing these materials. © 2015 Taylor & Francis Group, London.