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.

QSAR modeling of antitubercular activity of diverse organic compounds

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Lightweight user modeling – a case study

In the context of previous publications, we propose a new lightweight UM process, intended to work as a tourism recommender system in a commercial environment. The new process tackles issues like cold start, gray sheep and over specialization through a rich user model and the application of a gradual forgetting function to the collected user action history. Also, significant performance improvements were achieved regarding the previously proposed UM process.

Modeling group decision meeting participants with an Agent-based approach

This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

Modeling Allee Effect from Beta(p, 2) Densities

In this work we develop and investigate generalized populational growth models, adjusted from Beta(p, 2) densities, with Allee effect. The use of a positive parameter leads the presented generalization, which yields some more flexible models with variable extinction rates. An Allee limit is incorporated so that the models under study have strong Allee effect.

Desenvolvimento, complexo industrial da saúde e política industrial

O artigo situa a questão da saúde no contexto do desenvolvimento nacional e da política industrial. Tomou-se a idéia de corte estruturalista, marxista e schumpeteriano, onde a indústria e as inovações constituem os elementos determinantes do dinamismo das economias capitalistas e de sua posição relativa na economia mundial. Todos os países que se desenvolveram e passaram a competir em melhores condições com os países avançados associaram uma indústria forte com uma base endógena de conhecimento, de aprendizado e de inovação. Todavia, na área da saúde essa visão é problemática, uma vez que os interesses empresariais se movem pela lógica econômica do lucro e não para o atendimento das necessidades da saúde. A noção de complexo industrial da saúde constitui uma tentativa e fornecer um referencial teórico que permita articular duas lógicas distintas: a sanitária e a do desenvolvimento econômico. O trabalho procurou mostrar, com base em dados de comércio exterior, como a desconsideração da lógica do desenvolvimento nas políticas de saúde levou a uma situação de vulnerabilidade econômica do setor que pode limitar os objetivos de universalidade, eqüidade e integralidade. Nesse contexto, propõe-se uma ruptura cognitiva e política com as visões antagônicas que colocam, de um lado, as necessidades da saúde e, de outro, da indústria. Um país que pretende chegar a uma condição de desenvolvimento e de independência requer, ao mesmo tempo, indústrias fortes e inovadoras, e um sistema de saúde inclusivo e universal.

Navegação de um robô autónomo semi-industrial usando diferentes técnicas sensoriais

Mestrado em Engenharia Electrotécnica e de Computadores

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

User modeling and recommendation strategies for tourism

Mestrado em Engenharia Informática

Caracterização de antioxidantes com potencial interesse industrial

Mestrado em Engenharia Química

An application of structural equation modeling of test dispositional optimism as mediator or moderator in quality of life in patients with chronic disease

The aim of the present study was to test a hypothetical model to examine if dispositional optimism exerts a moderating or a mediating effect between personality traits and quality of life, in Portuguese patients with chronic diseases. A sample of 540 patients was recruited from central hospitals in various districts of Portugal. All patients completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, and quality of life. Structural equation modeling (SEM) was used to analyze the moderating and mediating effects. Results suggest that dispositional optimism exerts a mediator rather than a moderator role between personality traits and quality of life, suggesting that “the expectation that good things will happen” contributes to a better general well-being and better mental functioning.

Evaluating the efficiency of a vegetal coagulant in the treatment of industrial effluents

The present work aims at evaluating the efficiency of an organic polymer from vegetal source used as coagulant for treating different types of industrial effluents. This coagulant (Flox-QT) is obtained from the Black Acacia (Acacia mearnsii). The effluents studied were produced in petrochemical, leather, cork stoppers, metalworking, olive oil, glue, paint (printing), textile and paper industries. The parameters analyzed in the effluents before and after treatment were selected according to the type of wastewater and included pH, conductivity, apparent colour, turbidity, total suspended solids (TSS), chemical oxygen demand (COD) and some metals. The coagulant proved to be efficient for almost all effluents tested. The best results were obtained for the paper industry wastewater, with 91% removal of chemical oxygen demand and 95% of total suspended solids removal. The estimated cost of this treatment would be only 0.24 Euro per cubic meter of treated effluent, only regarding the price of the coagulant and the required dosage. The use of this coagulant is also adequate for the valorisation of the sludge obtained, which in this case could be recycled for paper production.

Desperdícios na cadeia logística no âmbito industrial

Projecto apresentado ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Logística Orientada por Prof. Doutor Gouveia

Monte Carlo modeling and simulations of the High Definition (HD120) micro MLC and validation against measurements for a 6 MV beam

Purpose: The most recent Varian® micro multileaf collimator(MLC), the High Definition (HD120) MLC, was modeled using the BEAMNRCMonte Carlo code. This model was incorporated into a Varian medical linear accelerator, for a 6 MV beam, in static and dynamic mode. The model was validated by comparing simulated profiles with measurements. Methods: The Varian® Trilogy® (2300C/D) accelerator model was accurately implemented using the state-of-the-art Monte Carlo simulation program BEAMNRC and validated against off-axis and depth dose profiles measured using ionization chambers, by adjusting the energy and the full width at half maximum (FWHM) of the initial electron beam. The HD120 MLC was modeled by developing a new BEAMNRC component module (CM), designated HDMLC, adapting the available DYNVMLC CM and incorporating the specific characteristics of this new micro MLC. The leaf dimensions were provided by the manufacturer. The geometry was visualized by tracing particles through the CM and recording their position when a leaf boundary is crossed. The leaf material density and abutting air gap between leaves were adjusted in order to obtain a good agreement between the simulated leakage profiles and EBT2 film measurements performed in a solid water phantom. To validate the HDMLC implementation, additional MLC static patterns were also simulated and compared to additional measurements. Furthermore, the ability to simulate dynamic MLC fields was implemented in the HDMLC CM. The simulation results of these fields were compared with EBT2 film measurements performed in a solid water phantom. Results: Overall, the discrepancies, with and without MLC, between the opened field simulations and the measurements using ionization chambers in a water phantom, for the off-axis profiles are below 2% and in depth-dose profiles are below 2% after the maximum dose depth and below 4% in the build-up region. On the conditions of these simulations, this tungsten-based MLC has a density of 18.7 g cm− 3 and an overall leakage of about 1.1 ± 0.03%. The discrepancies between the film measured and simulated closed and blocked fields are below 2% and 8%, respectively. Other measurements were performed for alternated leaf patterns and the agreement is satisfactory (to within 4%). The dynamic mode for this MLC was implemented and the discrepancies between film measurements and simulations are within 4%. Conclusions: The Varian® Trilogy® (2300 C/D) linear accelerator including the HD120 MLC was successfully modeled and simulated using the Monte CarloBEAMNRC code by developing an independent CM, the HDMLC CM, either in static and dynamic modes.