Seroprevalence of Helicobacter pylori infection in chagasic and nonchagasic patients from the same geographical region of Brazil

INTRODUCTION: In this study, we evaluated the seroprevalence of Helicobacter pylori infection among chagasic and non-chagasic subjects as well as among the subgroups of chagasic patients with the indeterminate, cardiac, digestive, and cardiodigestive clinical forms. METHODS: The evaluated subjects were from the Triângulo Mineiro region, Minas Gerais, Brazil. Chagasic patients showed positive reactions to the conventional serological tests used and were classified according to the clinical form of their disease. Immunoglobulin G antibodies specific to H. pylori were measured using a commercial enzyme-linked immunosorbent assay kit. RESULTS: The overall H. pylori prevalence was 77.1% (239/310) in chagasic and 69.1% (168/243) in non-chagasic patients. This difference was statistically significant even after adjustment for age and sex (odds ratio = 1.57; 95% confidence interval, 1.02-2.42; p = 0.04) in multivariate analysis. The prevalence of infection increased with age in the non-chagasic group (p = 0.007, χ2 for trend), but not in the chagasic group (p = 0.15, χ2 for trend). H. pylori infection was not associated with digestive or other clinical forms of Chagas disease (p = 0.27). CONCLUSIONS: Our findings demonstrate that chagasic patients have a higher prevalence of H. pylori compared to non-chagasic subjects; a similar prevalence was found among the diverse clinical forms of the disease. The factors contributing to the frequent co-infection with H. pylori and Trypanosoma cruzi as well as its effects on the clinical outcome deserve further study.

Paracoccidioidomycosis in the state of Maranhão, Brazil: geographical and clinical aspects

INTRODUCTION: The study aimed to show the situation of paracoccidioidomycosis in the state of Maranhão, Brazil. METHODS: This study is a descriptive case series developed in two stages. First, a survey of cases originating from the state of Maranhão at the Instituto de Doenças Tropicais Natan Portela, Piauí (IDTNP) from 1997 to 2007, and second, the clinical description of 29 cases diagnosed in the Centro de Referências em Doenças Infecciosas e Parasitárias, Maranhão (CREDIP) from 2004 to 2010. RESULTS: Two hundred and sixteen cases have been cataloged at the IDTNP. West, east, and central regions of the state of Maranhão recorded 90.3% of cases proving to be important areas for study. The western region, with a prevalence of 10.8/100,000 inhabitants, has a significantly higher proportion of cases than the northern, southern, and eastern regions (p < 0.05). The occurrence was higher in men with 89.3% of cases, and the male-to-female ratio was 8.4:1. The majority of patients were older than 20 years, lived in rural areas, and had farming or soil management as main occupation (73.8%). At CREDIP, 29 cases were diagnosed, of which 26 (89.6%) had multifocal manifestations. Mucous tissues were involved more (75.8%) frequently, followed by lymph nodes, skin, and lungs with 65.5%, 39% and 37.9 %, respectively. The diagnosis was made by combining direct examination, culture, and histopathology. CONCLUSIONS: The study shows the geographical distribution and the epidemiological and clinical aspects of paracoccidioidomycosis, revealing the significance of the disease to the state of Maranhão.

DYNAMOD – A dynamic agent based modelling framework for digital businesses

Digital Businesses have become a major driver for economic growth and have seen an explosion of new startups. At the same time, it also includes mature enterprises that have become global giants in a relatively short period of time. Digital Businesses have unique characteristics that make the running and management of a Digital Business much different from traditional offline businesses. Digital businesses respond to online users who are highly interconnected and networked. This enables a rapid flow of word of mouth, at a pace far greater than ever envisioned when dealing with traditional products and services. The relatively low cost of incremental user addition has led to a variety of innovation in pricing of digital products, including various forms of free and freemium pricing models. This thesis explores the unique characteristics and complexities of Digital Businesses and its implications on the design of Digital Business Models and Revenue Models. The thesis proposes an Agent Based Modeling Framework that can be used to develop Simulation Models that simulate the complex dynamics of Digital Businesses and the user interactions between users of a digital product. Such Simulation models can be used for a variety of purposes such as simple forecasting, analysing the impact of market disturbances, analysing the impact of changes in pricing models and optimising the pricing for maximum revenue generation or a balance between growth in usage and revenue generation. These models can be developed for a mature enterprise with a large historical record of user growth rate as well as for early stage enterprises without much historical data. Through three case studies, the thesis demonstrates the applicability of the Framework and its potential applications.

Dynamic delta hedging of autocallables under a discrete rebalancing context

This work tests different delta hedging strategies for two products issued by Banco de Investimento Global in 2012. The work studies the behaviour of the delta and gamma of autocallables and their impact on the results when delta hedging with different rebalancing periods. Given its discontinuous payoff and path dependency, it is suggested the hedging portfolio is rebalanced on a daily basis to better follow market changes. Moreover, a mixed strategy is analysed where time to maturity is used as a criterion to change the rebalancing frequency.

Geographical distribution of Trypanosoma cruzi in triatomine vectors in the State of Mato Grosso do Sul, Brazil

Introduction This work presents the initial findings of a molecular epidemiological investigation of Trypanosoma cruzi in triatomine insects in State of Mato Grosso do Sul. Methods A total of 511 triatomines from different regions of the state were examined. Deoxyribonucleic acid (DNA) was extracted from the intestinal contents of the insects using phenol-chloroform-isoamyl alcohol (25:24:1). Polymerase chain reaction (PCR) using primers 121/122 targeting DNA kinetoplast (kDNA) was then performed to identify T. cruzi, and positive samples were subjected to PCR using the primer pair TcSC5D-F/R followed by restriction fragment length polymorphism (RFLP) with the restriction enzymes SphI and HpaI (1 U/reaction), cloning and sequencing. Results One hundred samples were positive for T. cruzi, and three discrete typing units (DTUs) were identified (TcI, TcII, and TcBat). Triatoma sordida had the highest T. cruzi occurrence (83.3%), and DTUs were found in three samples: 58.3% of the samples were TcI, 33.3% were TcII and 8.3% were TcBat. There was a clear geographical distribution of the DTUs throughout the state, with TcI, TcII and TcBat located in the center, TcI located in the east, and TcII located in the west. Conclusions This study showed the occurrence of overlapping DTUs in State of Mato Grosso do Sul. The distributions of the DTUs were different, with TcI, TcII and TcBat in the center of the state, TcI predominantly in the east, and TcII in the west. Further studies may reveal a more defined mosaic distribution of DTUs in MS.

Nestle's dynamic forecasting process: Anticipating risks and opportunities

Nestlé’s Dynamic Forecasting Process: Anticipating Risks and Opportunities This Work Project discusses the Nestlé’s Dynamic Forecasting Process, implemented within the organization as a way of reengineering its performance management concept and processes, so as to make it more flexible and capable to react to volatile business conditions. When stressing the importance of demand planning to reallocate resources and enhance performance, Nescafé Dolce Gusto comes as way of seeking improvements on this forecasts’ accuracy and it is thus, by providing a more accurate model on its capsules’ sales, as well as recommending adequate implementations that positively contribute to the referred Planning Process, that value is brought to the Project

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Survey and dynamic behaviour of the Our Lady of Conception Church, Portugal

The Our Lady of Conception church is located in village of Monforte (Portugal) and is not in use nowadays. The church presents structural damage and, consequently, a study was carried out. The study involved the survey of the damage, dynamic identification tests under ambient vibration and the numerical analysis. The church is constituted by the central nave, the chancel, the sacristy and the corridor to access the pulpit. The masonry walls present different thickness, namely 0.65 m in the chancel, 0.70 m in the sacristy, 0.92 in the central nave and 0.65 m in the corridor. The masonry walls present 8 buttresses with different dimensions. The total longitudinal and transversal dimensions of the church are equal to 21.10 m and 14.26 m, respectively. The survey of the damage showed that, in general, the masonry walls are in good conditions, with exception of the transversal walls of the nave, which present severe cracks. The arches of the vault presents also severe cracks along the central nave. As consequence, the infiltrations have increased the degradation of the vault and paintings. Furthermore, the foundations present settlements in the Southwest direction. The dynamic identification test were carried out under the action of ambient excitation of the wind and using 12 piezoelectric accelerometers of high sensitivity. The dynamic identification tests allowed to estimate the dynamic properties of the church, namely frequencies, mode shapes and damping ratios. A FEM numerical model was prepared and calibrated, based on the first four experimental modes estimated in the dynamic identification tests. The average error between the experimental and numerical frequencies of the first four modes is equal to 5%. After calibration of the numerical model, pushover analyses with a load pattern proportional to the mass, in the transversal and longitudinal direction of the church, were performed. The results of the analysis numerical allow to conclude that the most vulnerable direction of the church is in the transversal one and the maximum load factor is equal to 0.35.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

Plataforma para suporte ao ciclo de vida de organizações virtuais e seleção dinâmica de parceiros e fornecedores

Tese de Doutoramento em Engenharia Industrial e de Sistemas

Jute/polypropylene composites: Effect of enzymatic modification on thermo-mechanical and dynamic mechanical properties

In this study, a high-performance composite was prepared from jute fabrics and polypropylene (PP). In order to improve the compatibility of the polar fibers and the non-polar matrix, alkyl gallates with different hydrophobic groups were enzymatically grafted onto jute fabric by laccase to increase the surface hydrophobicity of the fiber. The grafting products were characterized by FTIR. The results of contact angle and wetting time showed that the hydrophobicity of the jute fabrics was improved after the surface modification. The effect of the enzymatic graft modification on the properties of the jute/PP composites was evaluated. Results showed that after the modification, tensile and dynamic mechanical properties of composites improved, and water absorption and thickness swelling clearly decreased. However, tensile properties drastically decreased after a long period of water immersion. The thermal behavior of the composites was evaluated by TGA/DTG. The fiber-matrix morphology in the modified jute/PP composites was confirmed by SEM analysis of the tensile fractured specimens.

Dynamic piezoelectric stimulation enhances osteogenic differentiation of human adipose stem cells

This work reports on the influence of the substrate polarization of electroactive β-PVDF on human adipose stem cells (hASCs) differentiation under static and dynamic conditions. hASCs were cultured on different β-PVDF surfaces (non-poled and “poled -”) adsorbed with fibronectin and osteogenic differentiation was determined using a quantitative alkaline phosphatase assay. “Poled -” β-PVDF samples promote higher osteogenic differentiation, which is even higher under dynamic conditions. It is thus demonstrated that electroactive membranes can provide the necessary electromechanical stimuli for the differentiation of specific cells and therefore will support the design of suitable tissue engineering strategies, such as bone tissue engineering.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.