Reproductive outcomes in an area adjacent to a petrochemical plant in southern Brazil

OBJECTIVE: To evaluate possible adverse reproductive outcomes in an area adjacent to a petrochemical plant in southern Brazil. METHODS: A review of 17,113 birth records of the main hospital of the municipality of Montenegro, southern Brazil, from 1983 to 1998 was carried out. Three groups of cases were selected: (1) newborns with major congenital malformations; (2) newborns with low birth weight (<2,500 g); and (3) stillborns (>500 g). A control was assigned to each case. Controls were the first newborns weighing > or = 2,500 g without malformations and of case-matching sex. Mother's residence during pregnancy was used as an exposure parameter. Statistical analyses were performed using Chi-square test or Fisher test, odds ratio, 0.05 significance level, and 95% confidence interval. RESULTS: For unadjusted analysis, it was found a correlation between low birth weight and geographical proximity of mother's residence to the petrochemical plant (OR = 1.66; 95% CI = 1.01--2.72) or residence on the way of preferential wind direction (OR = 1.62; 95% CI = 1.03--2.56). When other covariates were added in the conditional logistic regression (maternal smoking habits, chronic disease and age), there was no association. CONCLUSIONS: Despite final results were negative, low birth weight could be a good parameter of environmental contamination and should be closely monitored in the studied area.

Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: Astudy case of the 1755 Lisbon tsunami in Algarve, Portugal (vol 182, pg 187, 2010)

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

On the solubility of three disperse anthraquinone dyes in supercritical carbon dioxide: new experimental data and correlation

Solubility measurements of quinizarin. (1,4-dihydroxyanthraquinone), disperse red 9 (1-(methylamino) anthraquinone), and disperse blue 14 (1,4-bis(methylamino)anthraquinone) in supercritical carbon dioxide (SC CO2) were carried out in a flow type apparatus, at a temperature range from (333.2 to 393.2) K and at pressures from (12.0 to 40.0) MPa. Mole fraction solubility of the three dyes decreases in the order quinizarin (2.9 x 10(-6) to 2.9.10(-4)), red 9 (1.4 x 10(-6) to 3.2 x 10(-4)), and blue 14 (7.8 x 10(-8) to 2.2 x 10(-5)). Four semiempirical density based models were used to correlatethe solubility of the dyes in the SC CO2. From the correlation results, the total heat of reaction, heat of vaporization plus the heat of solvation of the solute, were calculated and compared with the results presented in the literature. The solubilities of the three dyes were correlated also applying the Soave-Redlich-Kwong cubic equation of state (SRK CEoS) with classical mixing rules, and the physical properties required for the modeling were estimated and reported.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Optimization techniques for power distribution planning with uncertainties: a comparative study

Important research effort has been devoted to the topic of optimal planning of distribution systems. The non linear nature of the system, the need to consider a large number of scenarios and the increasing necessity to deal with uncertainties make optimal planning in distribution systems a difficult task. Heuristic techniques approaches have been proposed to deal with these issues, overcoming some of the inherent difficulties of classic methodologies. This paper considers several methodologies used to address planning problems of electrical power distribution networks, namely mixedinteger linear programming (MILP), ant colony algorithms (AC), genetic algorithms (GA), tabu search (TS), branch exchange (BE), simulated annealing (SA) and the Bender´s decomposition deterministic non-linear optimization technique (BD). Adequacy of theses techniques to deal with uncertainties is discussed. The behaviour of each optimization technique is compared from the point of view of the obtained solution and of the methodology performance. The paper presents results of the application of these optimization techniques to a real case of a 10-kV electrical distribution system with 201 nodes that feeds an urban area.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

Combining artificial intelligence techniques for the training of power system control centre operators

Control Centre operators are essential to assure a good performance of Power Systems. Operators’ actions are critical in dealing with incidents, especially severe faults, like blackouts. In this paper we present an Intelligent Tutoring approach for training Portuguese Control Centre operators in incident analysis and diagnosis, and service restoration of Power Systems, offering context awareness and an easy integration in the working environment.

Lesões da substância branca por ressonância magnética: uma avaliação entre as ponderações DWI e T2 FLAIR

RESUMO: Objetivos – Determinar a sensibilidade e especificidade das ponderações Difusão (DWI) e T2 Fluid-Attenuated Inversion Recovery (FLAIR) na avaliação de lesões da substância branca (SB) e verificar em que medida se complementam, por forma a criar um conjunto de boas práticas na RM cranioencefálica de rotina. Metodologia – Recorrendo-se a uma metodologia quantitativa, efetuou-se uma análise retrospetiva da qual foram selecionados 30 pacientes, 10 sem patologia e 20 com patologia (2 com EM, 7 com Leucoencefalopatia, 6 com doença microangiopática e 5 com patologia da substância branca indefinida). Obteve-se uma amostra de 60 imagens, nomeadamente: 30 imagens ponderadas em DWI e 30 em T2 FLAIR. Recorrendo ao programa Viewdex®, três observadores avaliaram um conjunto de imagens segundo sete critérios: visibilidade, deteção, homogeneidade, localização, margens e dimensões da lesão e capacidade de diagnóstico. Com os resultados obtidos recorreu-se ao cálculo de sensibilidade e especificidade pelas Curvas ROC, bem como à análise estatística, nomeadamente, Teste-T, Índice de Concordância Kappa e coeficiente de correlação de Pearson entre as variáveis em estudo. Resultados – Os resultados de sensibilidade e de especificidade obtidos para a ponderação T2 FLAIR foram superiores (0,915 e 0,038, respetivamente) aos da ponderação DWI (0,08 e 0,100, respetivamente). Não se verificaram variâncias populacionais significativas. Obteve-se uma elevada correlação linear entre as variáveis com um valor r situado entre 0,8 e 0,99. Verificou-se também uma variabilidade considerável entre os observadores. Conclusões – Dados os baixos valores de sensibilidade e especificidade obtidos para a DWI, sugere-se que esta deva ser incluída no protocolo de rotina de crânio como auxiliar no diagnóstico diferencial com outras patologias.

Estudo do desempenho de betões com incorporação de agregados finos provenientes de resíduos industriais

A crescente preocupação relacionada com a sustentabilidade ambiental e o risco de esgotamento de recursos naturais, tem levado à necessidade de encontrar novos materiais e novas técnicas construtivas. Nesse pressuposto, o presente trabalho tem como principal objetivo avaliar a viabilidade de utilização de resíduos provenientes de indústrias da região (lamas de cal e cinzas de biomassa) em produção de betões que possam vir a ser utilizados na construção civil. Neste sentido, desenvolveu-se uma campanha experimental com o intuito de comparar desempenho de sete tipos diferentes de betões: um de referência e seis com taxas de substituição de 20, 50 e 100% de agregados finos naturais por cinzas de biomassa e lamas de cal. A composição dos diferentes betões foi determinada pelo método de Faury, cumprindo-se as exigências na norma NP EN 206-1. O desempenho dos betões foi avaliado através da análise dos resultados de ensaios sobre o betão fresco (consistência, massa volúmica e teor de ar) e sobre o betão endurecido (massa volúmica, resistência à compressão, resistência à tração por compressão diametral, absorção de água por capilaridade e absorção de água por imersão). No presente trabalho, procedeu-se, também, à realização de ensaios químicos aos betões produzidos (lixiviação). No final do trabalho é feita uma discussão dos resultados experimentais e são evidenciadas as principais conclusões deste estudo.

Evaluation of IMRT and VMAT techniques with and without flattening filter using pareto optimal fronts

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.