The influence of number of counts in the myocardium in the determination of reproducible functional parameters in gated-SPECT studies simulated with GATE

Myocardial perfusion gated-single photon emission computed tomography (gated-SPECT) imaging is used for the combined evaluation of myocardial perfusion and left ventricular (LV) function. The aim of this study is to analyze the influence of counts/pixel and concomitantly the total counts in the myocardium for the calculation of myocardial functional parameters. Material and methods: Gated-SPECT studies were performed using a Monte Carlo GATE simulation package and the NCAT phantom. The simulations of these studies use the radiopharmaceutical 99mTc-labeled tracers (250, 350, 450 and 680MBq) for standard patient types, effectively corresponding to the following activities of myocardium: 3, 4.2, 5.4-8.2MBq. All studies were simulated using 15 and 30s/projection. The simulated data were reconstructed and processed by quantitative-gated-SPECT software, and the analysis of functional parameters in gated-SPECT images was done by using Bland-Altman test and Mann-Whitney-Wilcoxon test. Results: In studies simulated using different times (15 and 30s/projection), it was noted that for the activities for full body: 250 and 350MBq, there were statistically significant differences in parameters Motility and Thickness. For the left ventricular ejection fraction (LVEF), end-systolic volume (ESV) it was only for 250MBq, and 350MBq in the end-diastolic volume (EDV), while the simulated studies with 450 and 680MBq showed no statistically significant differences for global functional parameters: LVEF, EDV and ESV. Conclusion: The number of counts/pixel and, concomitantly, the total counts per simulation do not significantly interfere with the determination of gated-SPECT functional parameters, when using the administered average activity of 450MBq, corresponding to the 5.4MBq of the myocardium, for standard patient types.

Repeater-based hybrid wired/wireless PROFIBUS network simulator

This technical report describes the Repeater-Based Hybrid Wired/Wireless PROFIBUS Network Simulator that implements a simulation model of the repeater-based approach. This approach defines the mechanism to extend the PROFIBUS protocol to supprot wireless communication, in which the interconnection of the wired and wireless segments is done by a intermediate system operating at Physical Layer, as repeater.

A wireless sensor network platform for structural health monitoring: enabling accurate and synchronized measurements through COTS+custom-based design

Structural health monitoring has long been identified as a prominent application of Wireless Sensor Networks (WSNs), as traditional wired-based solutions present some inherent limitations such as installation/maintenance cost, scalability and visual impact. Nevertheless, there is a lack of ready-to-use and off-the-shelf WSN technologies that are able to fulfill some most demanding requirements of these applications, which can span from critical physical infrastructures (e.g. bridges, tunnels, mines, energy grid) to historical buildings or even industrial machinery and vehicles. Low-power and low-cost yet extremely sensitive and accurate accelerometer and signal acquisition hardware and stringent time synchronization of all sensors data are just examples of the requirements imposed by most of these applications. This paper presents a prototype system for health monitoring of civil engineering structures that has been jointly conceived by a team of civil, and electrical and computer engineers. It merges the benefits of standard and off-the-shelf (COTS) hardware and communication technologies with a minimum set of custom-designed signal acquisition hardware that is mandatory to fulfill all application requirements.

Neighbour list optimization for real LTE radio network

With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.

On the choice of posittioning and cluster size for fixed relay stations in a LTE network

The long term evolution (LTE) is one of the latest standards in the mobile communications market. To achieve its performance, LTE networks use several techniques, such as multi-carrier technique, multiple-input-multiple-output and cooperative communications. Inside cooperative communications, this paper focuses on the fixed relaying technique, presenting a way for determining the best position to deploy the relay station (RS), from a set of empirical good solutions, and also to quantify the associated performance gain using different cluster size configurations. The best RS position was obtained through realistic simulations, which set it as the middle of the cell's circumference arc. Additionally, it also confirmed that network's performance is improved when the number of RSs is increased. It was possible to conclude that, for each deployed RS, the percentage of area served by an RS increases about 10 %. Furthermore, the mean data rate in the cell has been increased by approximately 60 % through the use of RSs. Finally, a given scenario with a larger number of RSs, can experience the same performance as an equivalent scenario without RSs, but with higher reuse distance. This conduces to a compromise solution between RS installation and cluster size, in order to maximize capacity, as well as performance.

Relevant elderly gait features for functional fitness level grouping

Locomotor tasks characterization plays an important role in trying to improve the quality of life of a growing elderly population. This paper focuses on this matter by trying to characterize the locomotion of two population groups with different functional fitness levels (high or low) while executing three different tasks-gait, stair ascent and stair descent. Features were extracted from gait data, and feature selection methods were used in order to get the set of features that allow differentiation between functional fitness level. Unsupervised learning was used to validate the sets obtained and, ultimately, indicated that it is possible to distinguish the two population groups. The sets of best discriminate features for each task are identified and thoroughly analysed. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

The evolution of user mobility on the Eduroam network

The emergence of smartphones with Wireless LAN (WiFi) network interfaces brought new challenges to application developers. The expected increase of users connectivity will impact their expectations for example on the performance of background applications. Unfortunately, the number and breadth of the studies on the new patterns of user mobility and connectivity that result from the emergence of smartphones is still insufficient to support this claim. This paper contributes with preliminary results on a large scale study of the usage pattern of about 49000 devices and 31000 users who accessed at least one access point of the eduroam WiFi network on the campuses of the Lisbon Polytechnic Institute. Results confirm that the increasing number of smartphones resulted in significant changes to the pattern of use, with impact on the amount of traffic and users connection time.

A high level e-maintenance architecture to support on-site teams

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent modules to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. Further this paradigm shift towards “embedded intelligence”, supported by cross platform technologies, induces relevant organizational and functional changes on local maintenance teams. On the one hand, the possibility of outsourcing maintenance activities, with the warranty of a timely response, through the use of pervasive networking technologies and, on the other hand, the optimization of local maintenance staff are some examples of how IT is changing the scenario in maintenance. The concept of e-maintenance is, in this context, emerging as a new discipline with defined socio-economic challenges. This paper proposes a high level maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action.

Modeling of the lung impedance using a fractional order ladder network with constant phase elements

The self similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. The fractal geometry is typically characterized by a recurrent structure. This study investigates the identification of a model for the respiratory tree by means of its electrical equivalent based on intrinsic morphology. Measurements were obtained from seven volunteers, in terms of their respiratory impedance by means of its complex representation for frequencies below 5 Hz. A parametric modeling is then applied to the complex valued data points. Since at low-frequency range the inertance is negligible, each airway branch is modeled by using gamma cell resistance and capacitance, the latter having a fractional-order constant phase element (CPE), which is identified from measurements. In addition, the complex impedance is also approximated by means of a model consisting of a lumped series resistance and a lumped fractional-order capacitance. The results reveal that both models characterize the data well, whereas the averaged CPE values are supraunitary and subunitary for the ladder network and the lumped model, respectively.

Visual functional analysis in medical imaging

Aims of study: 1) Describe the importance of human visual system on lesion detection in medical imaging perception research; 2) Discuss the relevance of research in medical imaging addressing visual function analysis; 3) Identify visual function tests which could be conducted on observers prior to participation in medical imaging perception research.

Development of biocompatible and “smart” porous structures using CO2-assisted processes

Dissertação apresentada para a obtenção do grau de Doutor em Engenharia Química, especialidade Engenharia da Reacção Química, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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.

Functional role of macrobenthos in estuarine sediment dynamics

Thesis submitted to the Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

Chemical reaction network of flavylium ions in heterogeneous media

Dissertação apresentada para a obtenção do Grau de Doutor em Química, especialidade em Química-Física, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Functional disability of adults in Brazil: prevalence and associated factors

ABSTRACT OBJECTIVE To estimate the prevalence and factors associated with functional disability in adults in Brazil. METHODS We used information from the health supplement of the National Household Sample Survey in 2008. The dependent variable was the functional disability among adults of 18 to 65 years, measured by the difficulty of walking about 100 meters; independent variables were: health plan membership, region of residence, state of domicile, education level, household income, economic activity, self-perception of health, hospitalization, chronic diseases, age group, sex, and color. We calculated the gross odds ratios (OR), and their respective confidence intervals (95%), and adjusted them for variables of study by ordinal logistic regression, following hierarchical model. Sample weights were considered in all calculations. RESULTS We included 18,745 subjects, 74.0% of whom were women. More than a third of adults reported having functional disability. The disability was significantly higher among men (OR = 1.17; 95%CI 1.09;1.27), people from 35 to 49 years (OR = 1.30; 95%CI 1.17;1.45) and 50 to 65 years (OR = 1.38; 95%CI 1.24;1.54); economically inactive individuals (OR = 2.21; 95%CI 1.65;2.96); adults who reported heart disease (OR = 1.13; 95%CI 1.03;1.24), diabetes mellitus (OR = 1.16; 95%CI 1.05;1.29), arterial systemic hypertension (OR = 1.10; 95%CI 1.02;1.18), and arthritis/rheumatism (OR = 1.24; 95%CI 1.15;1.34); and participants who were admitted in the last 12 months (OR = 2.35; 95%CI 1.73;3.2). CONCLUSIONS Functional disability is common among Brazilian adults. Hospitalization is the most strongly associated factor, followed by economic activity, and chronic diseases. Sex, age, education, and income are also associated. Results indicate specific targets for actions that address the main factors associated with functional disabilities and contribute to the projection of interventions for the improvement of the well-being and promotion of adults' quality of life.