An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.

Evaluation of solubility and partition properties of ampicillin-based ionic liquids

In order to overcome the problems associated with low water solubility, and consequently low bioavailability of active pharmaceutical ingredients (APIs), herein we explore a modular ionic liquid synthetic strategy for improved APIs. Ionic liquids containing l-ampicillin as active pharmaceutical ingredient anion were prepared using the methodology developed in our previous work, using organic cations selected from substituted ammonium, phosphonium, pyridinium and methylimidazolium salts, with the intent of enhancing the solubility and bioavailability of l-ampicillin forms. In order to evaluate important properties of the synthesized API-ILs, the water solubility at 25 °C and 37 °C (body temperature) as well as octanol–water partition coefficients (Kow's) and HDPC micelles partition at 25 °C were measured. Critical micelle concentrations (CMC's) in water at 25 °C and 37 °C of the pharmaceutical ionic liquids bearing cations with surfactant properties were also determined from ionic conductivity measurements.

Spatial analysis of urban violence based on emergency room data

OBJECTIVE: To estimate the spatial intensity of urban violence events using wavelet-based methods and emergency room data. METHODS: Information on victims attended at the emergency room of a public hospital in the city of São Paulo, Southeastern Brazil, from January 1, 2002 to January 11, 2003 were obtained from hospital records. The spatial distribution of 3,540 events was recorded and a uniform random procedure was used to allocate records with incomplete addresses. Point processes and wavelet analysis technique were used to estimate the spatial intensity, defined as the expected number of events by unit area. RESULTS: Of all georeferenced points, 59% were accidents and 40% were assaults. There is a non-homogeneous spatial distribution of the events with high concentration in two districts and three large avenues in the southern area of the city of São Paulo. CONCLUSIONS: Hospital records combined with methodological tools to estimate intensity of events are useful to study urban violence. The wavelet analysis is useful in the computation of the expected number of events and their respective confidence bands for any sub-region and, consequently, in the specification of risk estimates that could be used in decision-making processes for public policies.

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

Proposta de um modelo de avaliação de websites de turismo de habitação

actividade de turismo de habitação tem crescido de forma sustentada ao longo dos últimos anos em Portugal e o recurso à internet como canal de comercialização deste serviço tem substituído gradualmente os restantes canais mais tradicionais. No entanto, esta generalização do recurso a websites, nesta e noutras áreas da actividade económica, não tem sido sempre sinónimo de qualidade, justificando assim a procura de sistemas de avaliação deste tipo de produto de software, que possam ser aplicados sistemática e eficazmente. Nesse sentido, foi desenvolvido este trabalho, no propósito de conseguir um modelo de avaliação de websites, específico para o turismo de habitação, na convicção de que para áreas específicas se exigem abordagens específicas. A pesquisa por modelos orientados para esta actividade não produziu qualquer resultado, ao contrário de outras áreas onde já existem modelos adequados, como sejam a área académica e outras. Daí a necessidade de conjugar ideias e conceitos mais genéricos, de fontes diversas, com elementos específicos de turismo de habitação, no intuito de os combinar e adequar aos objectivos deste trabalho. Assim, a partir de elementos da Norma ISO 9126; de conceitos de usabilidade, funcionalidade, credibilidade, e outros; da opção por uma abordagem de desempenho empresarial; de modelos já existentes, embora direccionados para outras áreas; e de um modelo exploratório de carácter empírico entretanto desenvolvido, foi concebido e implementado um modelo que se caracteriza no essencial, por ser estruturado em três níveis, contemplar um conjunto de trinta e oito atributos em avaliação, com maior incidência naqueles relacionados com aspectos que se considera terem maior influência no desempenho da actividade económica subjacente, e que tem uma ponderação variável do seu impacto no resultado final. No intuito de dar flexibilidade ao modelo e de contrariar a carga subjectiva resultante do processo de ponderação do impacto de cada atributo avaliado, foram implementados no modelo três cenários alternativos com ponderações distintas, cada um valorizando determinado tipo de atributos e desvalorizando outros. Naturalmente que, aquando da implementação do modelo exploratório foram já retiradas algumas conclusões sobre o panorama geral, todavia o modelo definitivo veio dar-lhes maior consistência e pormenor.

Oxidative Leaching of metals from electronic waste with solutions based on quaternary ammonium salts

The treatment of electric and electronic waste (WEEE) is a problem which receives ever more attention. An inadequate treatment results in harmful products ending up in the environment. This project intends to investigate the possibilities of an alternative route for recycling of metals from printed circuit boards (PCBs) obtained from rejected computers. The process is based on aqueous solutions composed of an etchant, either 0.2 M CuCl2.2H2O or 0.2 M FeCl3.6H2O, and a quaternary ammonium salt (quat) such as choline chloride or chlormequat. These solutions are reminiscent of deep eutectic solvents (DES) based on quats. DES are quite similar to ionic liquids (ILs) and are used as well as alternative solvents with a great diversity of physical properties, making them attractive for replacement of hazardous, volatile solvents (e.g. VOCs). A remarkable difference between genuine DES and ILs with the solutions used in this project is the addition of rather large quantities of water. It is shown the presence of water has a lot of advantages on the leaching of metals, while the properties typical for DES still remain. The oxidizing capacities of Cu(II) stem from the existence of a stable Cu(I) component in quat based DES and thus the leaching stems from the activity of the Cu(II)/Cu(I) redox couple. The advantage of Fe(III) in combination with DES is the fact that the Fe(III)/Fe(II) redox couple becomes reversible, which is not true in pure water. This opens perspectives for regeneration of the etching solution. In this project the leaching of copper was studied as a function of gradual increasing water content from 0 - 100w% with the same concentration of copper chloride or iron(III) chloride at room temperature and 80ºC. The solutions were also tested on real PCBs. At room temperature a maximum leaching effect for copper was obtained with 30w% choline chloride with 0.2 M CuCl2.2H2O. The leaching effect is still stronger at 80°C, b ut of course these solutions are more energy consuming. For aluminium, tin, zinc and lead, the leaching was faster at 80ºC. Iron and nickel dissolved easily at room temperature. The solutions were not able to dissolve gold, silver, rhodium and platinum.

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.