Air pollution at an urban traffic tunnel in Lisbon, Portugal

In this study, the results of chemical concentrations inside and outside of a Lisbon (Portugal) traffic tunnel were compared, during one week. They were obtained by Instrumental Neutron Activation Analysis (INAA). The tunnel values largely exceed the Air Ambient legislated values and the Pearson Correlations Coefficients point out to soil re-suspension/dispersed road dust (As, Ce, Eu, Hf, Fe, Mo, Sc, Zn), traffic-markers (Ba, Cr), tire wear (Cr, Zn), break wear (Fe, Zn, Ba, Cu, Sb), exhaust and motor oil (Zn) and sea-spray (Br, Na). On all days these elements inside the tunnel were more enriched than outside; significant statistical differences were found for Co (p=0.005), Br (p=0.008), Zn (p=0.01) and Sb (p=0.005), while enrichment factors of As and Sc are statistically identical. The highest values were found for As, Br, Zn and Sb, for both inside and outside the tunnel.

Comparison of indoor and outdoor fungi and particles in poultry units

A descriptive study was developed in order to compare indoor and outdoor air contamination caused by fungi and particles in seven poultry units. Twenty eight air samples of 25 litters were collected through the impaction method on malt extract agar. Air sampling and particles concentration measurement were done in the interior and also outside premises of the poultries’ pavilions. Regarding the fungal load in the air, indoor concentration of mold was higher than outside air in six poultry units. Twenty eight species / genera of fungi were identified indoor, being Scopulariopsis brevicaulis (40.5%) the most commonly isolated species and Rhizopus sp. (30.0%) the most commonly isolated genus. Concerning outdoor, eighteen species/genera of fungi were isolated, being Scopulariopsis brevicaulis (62.6%) also the most isolated. All the poultry farms analyzed presented indoor fungi different from the ones identified outdoors. Regarding particles’ contamination, PM2.5, PM5.0 and PM10 had a statistically significant difference (Mann-Whitney U test) between the inside and outside of the pavilions, with the inside more contaminated (p=.006; p=.005; p=.005, respectively). The analyzed poultry units are potential reservoirs of substantial amounts of fungi and particles and could therefore free them in the atmospheric air. The developed study showed that indoor air was more contaminated than outdoors, and this can result in emission of potentially pathogenic fungi and particles via aerosols from poultry units to the environment, which may post a considerable risk to public health and contribute to environmental pollution.

Occupational exposure to aflatoxin (AFB1) in poultry production

Aflatoxin B1 (AFB1) has been recognized to produce cancer in human liver. In addition, epidemiological and laboratory studies demonstrated that the respiratory system was a target for AFB1. Exposure occurs predominantly through the food chain, but inhalation represents an additional route of exposure. The present study aimed to examine AFB1 exposure among poultry workers in Portugal. Blood samples were collected from a total of 31 poultry workers from six poultry farms. In addition, a control group (n = 30) was included comprised of workers who undertook administrative tasks. Measurement of AFB1 in serum was performed by enzyme-linked immunosorbent assay (ELISA). For examining fungi contamination, air samples were collected through an impaction method. Air sampling was obtained in pavilion interior and outside the premises, since this was the place regarded as the reference location. Using molecular methods, toxicogenic strains (aflatoxin-producing) were investigated within the group of species belonging to Aspergillus flavus complex. Eighteen poultry workers (59%) had detectable levels of AFB1 with values ranging from <1 ng/ml to4.23 ng/ml and with a mean value of 2 ± 0.98ng/ml. AFB1 was not detected in the serum sampled from any of the controls. Aspergillus flavus was the fungal species third most frequently found in the indoor air samples analyzed (7.2%) and was the most frequently isolated species in air samples containing only Aspergillus genus (74.5%). The presence of aflatoxigenic strains was only confirmed in outdoor air samples from one of the units, indicating the presence of a source inside the building in at least one case. Data indicate that AFB1 inhalation represents an additional risk in this occupational setting that needs to be recognized, assessed, and prevented.

Convex Total Variation Denoising of Poisson Fluorescence Confocal Images With Anisotropic Filtering

Fluorescence confocal microscopy (FCM) is now one of the most important tools in biomedicine research. In fact, it makes it possible to accurately study the dynamic processes occurring inside the cell and its nucleus by following the motion of fluorescent molecules over time. Due to the small amount of acquired radiation and the huge optical and electronics amplification, the FCM images are usually corrupted by a severe type of Poisson noise. This noise may be even more damaging when very low intensity incident radiation is used to avoid phototoxicity. In this paper, a Bayesian algorithm is proposed to remove the Poisson intensity dependent noise corrupting the FCM image sequences. The observations are organized in a 3-D tensor where each plane is one of the images acquired along the time of a cell nucleus using the fluorescence loss in photobleaching (FLIP) technique. The method removes simultaneously the noise by considering different spatial and temporal correlations. This is accomplished by using an anisotropic 3-D filter that may be separately tuned in space and in time dimensions. Tests using synthetic and real data are described and presented to illustrate the application of the algorithm. A comparison with several state-of-the-art algorithms is also presented.

IOPT Petri Net State Space Generation Algorithm with Maximal-Step Execution Semantics

This paper presents an algorithm to efficiently generate the state-space of systems specified using the IOPT Petri-net modeling formalism. IOPT nets are a non-autonomous Petri-net class, based on Place-Transition nets with an extended set of features designed to allow the rapid prototyping and synthesis of system controllers through an existing hardware-software co-design framework. To obtain coherent and deterministic operation, IOPT nets use a maximal-step execution semantics where, in a single execution step, all enabled transitions will fire simultaneously. This fact increases the resulting state-space complexity and can cause an arc "explosion" effect. Real-world applications, with several million states, will reach a higher order of magnitude number of arcs, leading to the need for high performance state-space generator algorithms. The proposed algorithm applies a compilation approach to read a PNML file containing one IOPT model and automatically generate an optimized C program to calculate the corresponding state-space.

Comparação do cálculo de dose com os algoritmos Analytical Anisotropic Algorithm e Pencil Beam Convolution na patologia de pulmão

Mestrado em Radioterapia.

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Mestrado em Radioterapia

The use of non-standard CT conversion ramps for Monte Carlo verification of 6 MV prostate IMRT plans

Monte Carlo (MC) dose calculation algorithms have been widely used to verify the accuracy of intensity-modulated radiotherapy (IMRT) dose distributions computed by conventional algorithms due to the ability to precisely account for the effects of tissue inhomogeneities and multileaf collimator characteristics. Both algorithms present, however, a particular difference in terms of dose calculation and report. Whereas dose from conventional methods is traditionally computed and reported as the water-equivalent dose (Dw), MC dose algorithms calculate and report dose to medium (Dm). In order to compare consistently both methods, the conversion of MC Dm into Dw is therefore necessary. This study aims to assess the effect of applying the conversion of MC-based Dm distributions to Dw for prostate IMRT plans generated for 6 MV photon beams. MC phantoms were created from the patient CT images using three different ramps to convert CT numbers into material and mass density: a conventional four material ramp (CTCREATE) and two simplified CT conversion ramps: (1) air and water with variable densities and (2) air and water with unit density. MC simulations were performed using the BEAMnrc code for the treatment head simulation and the DOSXYZnrc code for the patient dose calculation. The conversion of Dm to Dw by scaling with the stopping power ratios of water to medium was also performed in a post-MC calculation process. The comparison of MC dose distributions calculated in conventional and simplified (water with variable densities) phantoms showed that the effect of material composition on dose-volume histograms (DVH) was less than 1% for soft tissue and about 2.5% near and inside bone structures. The effect of material density on DVH was less than 1% for all tissues through the comparison of MC distributions performed in the two simplified phantoms considering water. Additionally, MC dose distributions were compared with the predictions from an Eclipse treatment planning system (TPS), which employed a pencil beam convolution (PBC) algorithm with Modified Batho Power Law heterogeneity correction. Eclipse PBC and MC calculations (conventional and simplified phantoms) agreed well (<1%) for soft tissues. For femoral heads, differences up to 3% were observed between the DVH for Eclipse PBC and MC calculated in conventional phantoms. The use of the CT conversion ramp of water with variable densities for MC simulations showed no dose discrepancies (0.5%) with the PBC algorithm. Moreover, converting Dm to Dw using mass stopping power ratios resulted in a significant shift (up to 6%) in the DVH for the femoral heads compared to the Eclipse PBC one. Our results show that, for prostate IMRT plans delivered with 6 MV photon beams, no conversion of MC dose from medium to water using stopping power ratio is needed. In contrast, MC dose calculations using water with variable density may be a simple way to solve the problem found using the dose conversion method based on the stopping power ratio.

Personatv

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Jornalismo.

Sistema de multiprocessamento para simulação de N-corpos em FPGA

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Comparison of the pencil beam convolution algorithm and the analytical anisotropic algorithm in breast tumors

The calculation of the dose is one of the key steps in radiotherapy planning1-5. This calculation should be as accurate as possible, and over the years it became feasible through the implementation of new algorithms to calculate the dose on the treatment planning systems applied in radiotherapy. When a breast tumour is irradiated, it is fundamental a precise dose distribution to ensure the planning target volume (PTV) coverage and prevent skin complications. Some investigations, using breast cases, showed that the pencil beam convolution algorithm (PBC) overestimates the dose in the PTV and in the proximal region of the ipsilateral lung. However, underestimates the dose in the distal region of the ipsilateral lung, when compared with analytical anisotropic algorithm (AAA). With this study we aim to compare the performance in breast tumors of the PBC and AAA algorithms.

A SON Enhanced Algorithm for Observed Time Differences Based Geolocation in Real 3G Networks

Conferência - 16th International Symposium on Wireless Personal Multimedia Communications (WPMC)- Jun 24-27, 2013