Pair trading: Clustering based on principal component analysis

This study focuses on the implementation of several pair trading strategies across three emerging markets, with the objective of comparing the results obtained from the different strategies and assessing if pair trading benefits from a more volatile environment. The results show that, indeed, there are higher potential profits arising from emerging markets. However, the higher excess return will be partially offset by higher transaction costs, which will be a determinant factor to the profitability of pair trading strategies. Also, a new clustering approach based on the Principal Component Analysis was tested as an alternative to the more standard clustering by Industry Groups. The new clustering approach delivers promising results, consistently reducing volatility to a greater extent than the Industry Group approach, with no significant harm to the excess returns.

Ion-beam sources based on superionic solid electrolytes

An ion emitter consisting of a sharp silver tip covered in RbAg4I5 solid electrolyte film has been developed and studied. An accelerating potential is applied and Ag+ ions are emitted from the tip’s apex by field evaporation. The emitted ions are collected by a Faraday cup, producing a current on the pico/nanoampere level which is read by an electrometer. The tips were produced mechanically by sandpaper polishing. The sharpest tip produced had a 2:4 m apex radius. Two deposition methods were studied: thermal vacuum and pulsed laser deposition. The best tip produced a peak current value of 96nA at 180oC, and a quasi-stable 4nA emission current at 160oC, both using an extraction potential of 10kV . The emission dependence on time, temperature and accelerating potential has been studied. Deposited films were characterized by X-ray diffraction (XRD), profilometry, optical and Scanning Electron Microscope (SEM) and Secondary Ion Mass Spectroscopy (SIMS) measurements. Several ion emitters were developed, the latter ones were all able to maintain stable high ion emissions for long periods of time. This investigation was a continuation of an ongoing project backed by the European Space Agency, with the objective of making a proof of concept of this kind of ion emitter with potential application on ion thrusters for orbiting satellites. Going forward, it would be interesting to make a finer analysis of the electrolyte’s conductivity at high temperatures, explore Wien Effect-based emission and to further develop a multi-tip ion emitter prototype.

An agent-based model to assess the attractiveness of industrial estates

This article describes the main approaches adopted in a study focused on planning industrial estates on a sub-regional scale. The study was supported by an agent-based model, using firms as agents to assess the attractiveness of industrial estates. The simulation was made by the NetLogo toolkit and the environment represents a geographical space. Three scenarios and four hypotheses were used in the simulation to test the impact of different policies on the attractiveness of industrial estates. Policies were distinguished by the level of municipal coordination at which they were implemented and by the type of intervention. In the model, the attractiveness of industrial estates was based on the level of facilities, amenities, accessibility and on the price of land in each industrial estate. Firms are able to move and relocate whenever they find an attractive estate. The relocating firms were selected by their size, location and distance to an industrial estate. Results show that a coordinated policy among municipalities is the most efficient policy to promote advanced-qualified estates. In these scenarios, it was observed that more industrial estates became attractive, more firms were relocated and more vacant lots were occupied. Furthermore, the results also indicate that the promotion of widespread industrial estates with poor-quality infrastructures and amenities is an inefficient policy to attract firms.

An evolutionary multi-objective optimization system for earthworks

Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Assessment of distinctive road runoff quality in coastal areas, based on a monitoring case study

High levels of marine salt deposition present in coastal areas have a relevant effect on road runoff characteristics. This study assesses this effect with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included 30 rainfall events, in different weather, traffic, and salt deposition conditions. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological, and traffic parameters were continuously measured. The salt deposition rates were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The relation between road runoff pollutants and independent variables associated with weather, traffic, and salt deposition conditions was assessed. Significant correlations among pollutants were observed. A high salinity concentration and its influence on the road runoff were confirmed. Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed.

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Racial inequalities in the socioeconomic, demographic and health conditions of elderly from Maranhão State, Legal Amazon, Brazil: a population-based study

Aging with quality of life does not occur equally among the racial groups of Brazilian elderly, and few studies have analyzed this issue in the states of the Brazilian Legal Amazon. The objective of this study was to investigate racial inequalities in the socioeconomic, demographic and health conditions of elderly residents of Maranhão state, Brazil. The present work is a cross-sectional study of 450 elders aged 60 years or older included in the 2008 National Household Sample Survey. The prevalence of socioeconomic, demographic, health and habit indicators and of risk factors were estimated in white, brown and black racial categories that were self-reported by the survey participants. The chi-square test was used for comparisons (a=5%). The majority of the elderly respondents identified themselves as brown (66.4%) or white (23.3%). There were significant socioeconomic, demographic, habit and lifestyle differences among the racial groups. Most of the black and brown elderly lived alone, reported lower educational levels and were in the lowest quintile for income. These respondents were also highly dependent on the Unified Health System (Sistema Único de Saúde - SUS), exhibited low rates of screening mammograms and lower physical activity levels and had a greater proportion of smokers. However, there was no difference in the prevalence of health indicators or in the proportion of elderly by gender, age, social role in the family or the urban-rural location of the household. These results indicate the presence of racial inequalities in the socioeconomic and demographic status and in the practice of healthy habits and lifestyles among elderly from Maranhão, but suggest equity in health status. The results also suggest the complexity and challenges of interlinking race with socioeconomic aspects, and the findings reinforce the need for the implementation of public policies for these population groups.

Yield of essential oil and safrole content based on fresh and dry biomass of long pepper in the Brazilian Amazon

Long pepper (Piper hispidinervum) is an Amazonian species of commercial interest due to the production of safrole. Drying long pepper biomass to extract safrole is a time consuming and costly process that can also result in the contamination of the material by microorganisms. The objective of this study was to analyze the yield of essential oil and safrole content of fresh and dried biomass of long pepper accessions maintained in the Active Germoplasm Bank of Embrapa Acre, in the state of Acre, Brazil, aiming at selecting genotypes with best performance on fresh biomass to recommend to the breeding program of the species. Yield of essential oil and safrole content were assessed in 15 long pepper accessions. The essential oil extraction was performed by hydrodistillation and analyzed by gas chromatography. A joint analysis of experiments was performed and the means of essential oil yield and safrole content for each biomass were compared by Student's t-test. There was variability in the essential oil yield and safrole content. There was no difference between the types of biomass for oil yield; however to the safrole content there was difference. Populations 9, 10, 12 and 15 had values of oil yield between 4.1 and 5.3%, and safrole content between 87.2 and 94.3%. The drying process does not interfere in oil productivity. These populations have potential for selection to the long pepper breeding program using oil extraction in the fresh biomass

Critical analyses of the introduction of liquid-based cytology in a public health service of the state of São Paulo, Brazil

OBJECTIVE The aim of this study was to compare the performance of the current conventional Pap smear with liquid-based cytology (LBC) preparations. STUDY DESIGN Women routinely undergoing their cytopathological and histopathological examinations at Fundação Oncocentro de São Paulo (FOSP) were recruited for LBC. Conventional smears were analyzed from women from other areas of the State of São Paulo with similar sociodemographic characteristics. RESULTS A total of 218,594 cases were analyzed, consisting of 206,999 conventional smears and 11,595 LBC. Among the conventional smears, 3.0% were of unsatisfactory preparation; conversely, unsatisfactory LBC preparations accounted for 0.3%. The ASC-H (atypical squamous cells - cannot exclude high-grade squamous intraepithelial lesion) frequency did not demonstrate any differences between the two methods. In contrast, the incidence of ASC-US (atypical squamous cells of undetermined significance) was almost twice as frequent between LBC and conventional smears, at 2.9 versus 1.6%, respectively. An equal percentage of high-grade squamous intraepithelial lesions were observed for the two methods, but not for low-grade squamous intraepithelial lesions, which were more significantly observed in LBC preparations than in conventional smears (2.2 vs. 0.7%). The index of positivity was importantly enhanced from 3.0% (conventional smears) to 5.7% (LBC). CONCLUSIONS LBC performed better than conventional smears, and we are truly confident that LBC can improve public health strategies aimed at reducing cervical lesions through prevention programs.

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.

Coordenação de segurança em obra: metodologia, técnicas e ferramentas

Dissertação de mestrado integrado em Engenharia Civil