Geomecânica aplicada à estabilidade de explorações mineiras bench and fill: o caso do jazigo de Feitais, Minas de Aljustrel

Este trabalho pretende abordar a importância de um estudo geomecânico no apoio à otimização e estabilidade de explorações subterrâneas por subníveis, com criação de bancadas e posterior enchimento. O presente envolveu um estudo geológico-geotécnico em quinze galerias situadas a muro, teto e corpo da mineralização com o levantamento das características mais relevantes do maciço rochoso para aplicação das classificações geomecânicas, englobando uma amostragem de mais de 1780 descontinuidades, obtendo um modelo cartográfico subterrâneo com um panorama geral da qualidade do maciço rochoso intercetado pelas escavações nas diferentes zonas. Os dados dos levantamentos de campo levaram à criação de uma base de dados com a aplicação das classificações geomecânicas Q-System, RMR e GSI, por galeria e, em seguida, por zona, com proposta de classe de sustimento a aplicar em cada local, pelo ábaco de Barton, em conjunto com a determinação de parâmetros geomecânicos fundamentais ao refinamento do conhecimento geológico-geotécnico das unidades litológicas em estudo. Na parte final, focando a localização da massa mineralizada de Feitais é efetuada uma abordagem relativa à estabilidade das cavidades geradas pelo desmonte em bancada entre subníveis, com respetivo dimensionamento das larguras admissíveis, em condições de segurança, através da relação entre o número de estabilidade e raio hidráulico, pelo método do gráfico de estabilidade. Com esta metodologia de caracterização geológico geotécnica, é pretendido efetuar um ponto de partida à criação de um modelo geomecânico comportamental do jazigo de Feitais, Mina de Aljustrel, contando com um processo inicial de apoio ao planeamento mineiro aplicado ao método de desmonte em bancada e posterior enchimento por subníveis, atuando nos parâmetros de estabilidade e apoio à extração, favorecendo assim a segurança das operações de trabalho em conjunto com um apoio de otimização da extração.

American cutaneous leishmaniasis in the Pontal of Paranapanema - SP, Brazil: ecological and entomological aspects

American cutaneous leishmaniasis (ACL) occurs in epidemic outbreaks and in sporadic cases with small annual variation in the Pontal of Paranapanema, SP. There is little research on the sandfly fauna of this region. The last outbreaks were related to the Movement of the Landless Workers (MST) and with the ecological tourism in preserved forest of the Parque Estadual do Morro do Diabo (PEMD). AIM: identification of the sandfly fauna within the PEMD, mainly anthropophilic species already incriminated as vectors of ACL, as well as their seasonality, hourly frequency and data of the behavior. M&M: The captures were undertaken with CDC light and Shannon traps from 6:00 pm to 10:00 pm, monthly from May 2000 to December 2001. The temperature and relative humidity data were registered at hourly intervals. RESULTS: The captured species were: Brumptomyia brumpti, Nyssomyia neivai, Nyssomyia whitmani, Pintomyia fischeri and Pintomyia pessoai. The P. pessoai predominated (34.39%) and N. neivai was less found (0.74%), only being captured in CDC traps. Shannon trap captured more sandflies (63.01%) than the CDC traps (36.99%). Despite the environmental degradation anthropophilic species, indicates favorable bioecological conditions for persistence of vectors and potential transmission of leishmaniasis.

User Profiling and Knowledge Extraction For Tourism

O sector do turismo é uma área francamente em crescimento em Portugal e que tem desenvolvido a sua divulgação e estratégia de marketing. Contudo, apenas se prende com indicadores de desempenho e de oferta instalada (número de quartos, hotéis, voos, estadias), deixando os indicadores estatísticos em segundo plano. De acordo com o “ Travel & tourism Competitiveness Report 2013”, do World Economic Forum, classifica Portugal em 72º lugar no que respeita à qualidade e cobertura da informação estatística, disponível para o sector do Turismo. Refira-se que Espanha ocupa o 3º lugar. Uma estratégia de mercado, sem base analítica, que sustente um quadro de orientações específico e objetivo, com relevante conhecimento dos mercados alvo, dificilmente é compreensível ou até mesmo materializável. A implementação de uma estrutura de Business Intelligence que permita a realização de um levantamento e tratamento de dados que possibilite relacionar e sustentar os resultados obtidos no sector do turismo revela-se fundamental e crucial, para que sejam criadas estratégias de mercado. Essas estratégias são realizadas a partir da informação dos turistas que nos visitam, e dos potenciais turistas, para que possam ser cativados no futuro. A análise das características e dos padrões comportamentais dos turistas permite definir perfis distintos e assim detetar as tendências de mercado, de forma a promover a oferta dos produtos e serviços mais adequados. O conhecimento obtido permite, por um lado criar e disponibilizar os produtos mais atrativos para oferecer aos turistas e por outro informá-los, de uma forma direcionada, da existência desses produtos. Assim, a associação de uma recomendação personalizada que, com base no conhecimento de perfis do turista proceda ao aconselhamento dos melhores produtos, revela-se como uma ferramenta essencial na captação e expansão de mercado.

PRETERM BIRTH AND FETAL GROWTH RESTRICTION IN HIV-INFECTED BRAZILIAN PREGNANT WOMEN

Introduction: Maternal HIV infection and related co-morbidities may have two outstanding consequences to fetal health: mother-to-child transmission (MTCT) and adverse perinatal outcomes. After Brazilian success in reducing MTCT, the attention must now be diverted to the potentially increased risk for preterm birth (PTB) and intrauterine fetal growth restriction (IUGR). Objective: To determine the prevalence of PTB and IUGR in low income, antiretroviral users, publicly assisted, HIV-infected women and to verify its relation to the HIV infection stage. Patients and Methods: Out of 250 deliveries from HIV-infected mothers that delivered at a tertiary public university hospital in the city of Vitória, state of Espírito Santo, Southeastern Brazil, from November 2001 to May 2012, 74 single pregnancies were selected for study, with ultrasound validated gestational age (GA) and data on birth dimensions: fetal weight (FW), birth length (BL), head and abdominal circumferences (HC, AC). The data were extracted from clinical and pathological records, and the outcomes summarized as proportions of preterm birth (PTB, < 37 weeks), low birth weight (LBW, < 2500g) and small (SGA), adequate (AGA) and large (LGA) for GA, defined as having a value below, between or beyond the ±1.28 z/GA score, the usual clinical cut-off to demarcate the 10th and 90th percentiles. Results: PTB was observed in 17.5%, LBW in 20.2% and SGA FW, BL, HC and AC in 16.2%, 19.1%, 13.8%, and 17.4% respectively. The proportions in HIV-only and AIDS cases were: PTB: 5.9 versus 27.5%, LBW: 14.7% versus 25.0%, SGA BW: 17.6% versus 15.0%, BL: 6.0% versus 30.0%, HC: 9.0% versus 17.9%, and AC: 13.3% versus 21.2%; only SGA BL attained a significant difference. Out of 15 cases of LBW, eight (53.3%) were preterm only, four (26.7%) were SGA only, and three (20.0%) were both PTB and SGA cases. A concomitant presence of, at least, two SGA dimensions in the same fetus was frequent. Conclusions: The proportions of preterm birth and low birth weight were higher than the local and Brazilian prevalence and a trend was observed for higher proportions of SGA fetal dimensions than the expected population distribution in this small casuistry of newborn from the HIV-infected, low income, antiretroviral users, and publicly assisted pregnant women. A trend for higher prevalence of PTB, LBW and SGA fetal dimensions was also observed in infants born to mothers with AIDS compared to HIV-infected mothers without AIDS.

Integrated data model and DSL modifications

Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Antimicrobial use, incidence, etiology and resistance patterns in bacteria causing ventilator-associated pneumonia in a clinical-surgical intensive care unit

INTRODUCTION : Antimicrobial resistance is an increasing threat in hospitalized patients, and inappropriate empirical antimicrobial therapy is known to adversely affect outcomes in ventilator-associated pneumonia (VAP). The aim of this study was to evaluate antimicrobial usage, incidence, etiology, and antimicrobial resistance trends for prominent nosocomial pathogens causing ventilator-associated pneumonia in a clinical-surgical intensive care unit (ICU). METHODS : Gram-negative bacilli and Staphylococcus aureus causing VAP, as well as their antimicrobial resistance patterns and data on consumption (defined daily dose [DDD] per 1,000 patient days) of glycopeptides, extended-spectrum cephalosporins, and carbapenems in the unit were evaluated in two different periods (A and B). RESULTS: Antimicrobial use was high, mainly of broad-spectrum cephalosporins, with a significant increase in the consumption of glycopeptides (p < 0.0001) and carbapenems (p < 0.007) in period B. For Acinetobacter baumannii and members of the Enterobacteriaceae family, 5.27- and 3.06-fold increases in VAPs, respectively, were noted, and a significant increase in resistance rates was found for imipenem-resistant A. baumannii (p = 0.003) and third-generation cephalosporins-resistant Enterobacteriaceae (p = 0.01) isolates in this same period. CONCLUSIONS: Our results suggest that there is a link between antibiotics usage at institutional levels and resistant bacteria. The use of carbapenems was related to the high rate of resistance in A. baumannii and therefore a high consumption of imipenem/meropenem could play a major role in selective pressure exerted by antibiotics in A. baumannii strains.

Risks and benefits of hormone replacement therapy in older men

The use of testosterone in older men, known as male hormonal replacement therapy or androgen replacement therapy, has become of increasing interest to both the medical and lay communities over the past decade. Even though the knowledge of the potential benefits and risks of male Androgen Replacement Therapy has increased dramatically, there is still much that needs to be determined. Although there are a number of potential benefits of male Androgen Replacement Therapy and data concerning clinical effects of such replacement have accumulated, as yet there have not been any large multicenter randomized controlled trials of this therapy. It is the purpose of this article to review what is currently known about the possible risks and benefits of male Androgen Replacement Therapy by discussing the clinical trials to date.

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.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Clustering-based approach for categorizing pregnant women in obstetrics and maternity care

When a pregnant woman is guided to a hospital for obstetrics purposes, many outcomes are possible, depending on her current conditions. An improved understanding of these conditions could provide a more direct medical approach by categorizing the different types of patients, enabling a faster response to risk situations, and therefore increasing the quality of services. In this case study, the characteristics of the patients admitted in the maternity care unit of Centro Hospitalar of Porto are acknowledged, allowing categorizing the patient women through clustering techniques. The main goal is to predict the patients’ route through the maternity care, adapting the services according to their conditions, providing the best clinical decisions and a cost-effective treatment to patients. The models developed presented very interesting results, being the best clustering evaluation index: 0.65. The evaluation of the clustering algorithms proved the viability of using clustering based data mining models to characterize pregnant patients, identifying which conditions can be used as an alert to prevent the occurrence of medical complications.

Occupational stress and coping among portuguese military police officers

This study describes the professional experience of military police officers from the Portuguese Republican National Guard (N = 95). We focused on the main sources and consequences of stress and the coping strategies used to deal with stress. The evaluation protocol included one closed-ended question and four open-ended questions. Data analysis of meaningful text segments was conceptually based and data categorization followed deductive content analysis. Results allowed the identification of 483 meaning units. Factors intrinsic to the job and the relationships at work were the main stressors referred by participants. The consequences of stressors were evident at an individual level, affecting family, psychological, and physical/health domains. The coping strategies used to deal with the main source of stress in the professional career were focused on problem solving (e.g., active confrontation) and emotional regulation (e.g., situation acceptance). Practical implications and future avenues of research with these professionals are discussed.

Pervasive patient timeline

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

Apoio à decisão na análise inteligente de reclamações

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação