37 resultados para Novel methodology

em Universidade do Minho


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Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation.

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Degree of Doctor of Philosophy of Structural/Civil Engineering

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Doctoral Dissertation for PhD degree in Chemical and Biological Engineering

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The development of organic materials displaying high two-photon absorption (TPA) has attracted much attention in recent years due to a variety of potential applications in photonics and optoelectronics, such as three-dimensional optical data storage, fluorescence imaging, two-photon microscopy, optical limiting, microfabrication, photodynamic therapy, upconverted lasing, etc. The most frequently employed structural motifs for TPA materials are donor–pi bridge–acceptor (D–pi–A) dipoles, donor–pi bridge–donor (D–pi–D) and acceptor–pi bridge-acceptor (A–pi–A) quadrupoles, octupoles, etc. In this work we present the synthesis and photophysical characterization of quadrupolar heterocyclic systems with potential applications in materials and biological sciences as TPA chromophores. Indole is a versatile building block for the synthesis of heterocyclic systems for several optoelectronic applications (chemosensors, nonlinear optical, OLEDs) due to its photophysical properties and donor electron ability and 4H-pyran-4-ylidene fragment is frequently used for the synthesis of red light-emitting materials. On the other hand, 2-(2,6-dimethyl-4H-pyran-4-ylidene)malononitrile (1) and 1,3-diethyl-dihydro-5-(2,6-dimethyl-4H-pyran-4-ylidene)-2-thiobarbituric (2) units are usually used as strong acceptor moieties for the preparation of π-conjugated systems of the push-pull type. These building blocks were prepared by Knoevenagel condensation of the corresponding ketone precursor with malononitrile or 1,3-diethyl-dihydro-2-thiobarbituric acid. The new quadrupolar 4H-pyran-4-ylidene fluorophores (3) derived from indole were prepared through condensation of 5-methyl-1H-indole-3-carbaldehyde with the acceptor precursors 1 and 2, in the presence of a catalytical amount of piperidine. The new compounds were characterized by the usual spectroscopic techniques (UV-vis., FT-IR and multinuclear NMR - 1H, 13C).

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This paper presents a novel architecture of a bidirectional bridgeless interleaved converter for battery chargers of electric vehicles (EVs). The proposed converter is composed by two power stages: an ac-dc converter that is used to interface the power grid and the dc-link, and a dc-dc converter that is used to interface the dc-link and the batteries. The ac-dc converter is an interleaved bridgeless bidirectional boost-type converter and the dc-dc converter is a bidirectional buck-boost-type converter. The proposed converter works with sinusoidal grid current and with high power factor for all operating power levels, and in both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. In the paper is described in detail the proposed converter for EV battery chargers: the circuit topology, the principle of operation, the power control theory, and the current control strategy. Several simulation results for both G2V and V2G operation modes are presented.

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This paper presents a novel concept of unidirectional bridgeless combined boost-buck converter for electric vehicles (EVs) battery chargers. The proposed converter is composed by two power stages: an ac-dc front-end converter used to interface the power grid and the dc-link, and a dc-dc back-end converter used to interface the dc-link and the batteries. The ac-dc converter is a bridgeless boost-type converter and the dc-dc converter is an interleaved buck-type converter. The proposed converter operates with sinusoidal grid current and unitary power factor for all operating power levels. Along the paper is described in detail the proposed converter for EV battery chargers: the circuit topology, the different stages describing the principle of operation, the power control theory, and the current control strategy, for both converters. Along the paper are presented several simulation results for a maximum power of 3.5 kW.

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Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

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Ramos, D., Arezes, P. M., & Afonso, P. (2015). A systematic approach for externalities in occupational safety through the use of the delphi methodology. Paper presented at the Occupational Safety and Hygiene III - Selected Extended and Revised Contributions from the International Symposium on Safety and Hygiene.

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The pavement recycling allows to reuse reclaimed asphalt pavement (RAP) or other waste materials in new asphalt mixtures for road construction or rehabilitation, thus re-ducing the use of virgin materials (aggregates and bitumen). Thus, the main aim of this study is to minimize the use of natural resources through the reuse of three waste materials: HDPE, mo-tor oil and RAP. Different amounts of waste motor oil and HDPE were added to an asphalt binder with 50% aged bitumen. The best solutions to produce the modified binders (4.5 to 5.0% HDPE and 10 % waste motor oil) performed as well as a conventional bitumen although they only used 35 % of virgin bitumen. Asphalt mixtures with 50 % RAP were produced with the selected modified binders, improving some characteristics in comparison with conventional asphalt mixtures. In conclusion, these wastes can revive in new asphalt mixtures.

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Novel input modalities such as touch, tangibles or gestures try to exploit human's innate skills rather than imposing new learning processes. However, despite the recent boom of different natural interaction paradigms, it hasn't been systematically evaluated how these interfaces influence a user's performance or whether each interface could be more or less appropriate when it comes to: 1) different age groups; and 2) different basic operations, as data selection, insertion or manipulation. This work presents the first step of an exploratory evaluation about whether or not the users' performance is indeed influenced by the different interfaces. The key point is to understand how different interaction paradigms affect specific target-audiences (children, adults and older adults) when dealing with a selection task. 60 participants took part in this study to assess how different interfaces may influence the interaction of specific groups of users with regard to their age. Four input modalities were used to perform a selection task and the methodology was based on usability testing (speed, accuracy and user preference). The study suggests a statistically significant difference between mean selection times for each group of users, and also raises new issues regarding the “old” mouse input versus the “new” input modalities.

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Tese de Doutoramento em Ciências da Saúde

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Tese de Doutoramento em Engenharia Química e Biológica.

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The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

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Efficient liposome disruption inside the cells is a key for success with any type of drug delivery system. The efficacy of drug delivery is currently evaluated by direct visualization of labeled liposomes internalized by cells, not addressing objectively the release and distribution of the drug. Here, we propose a novel method to easily assess liposome disruption and drug release into the cytoplasm. We propose the encapsulation of the cationic dye Hoechst 34,580 to detect an increase in blue fluorescence due to its specific binding to negatively charged DNA. For that, the dye needs to be released inside the cell and translocated to the nucleus. The present approach correlates the intensity of detected fluorescent dye with liposome disruption and consequently assesses drug delivery within the cells.

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Novel multifunctional porous films have been developed by the integration of magnetic CoFe2O4 (CFO) nanoparticles into poly(vinylidene fluoride)-Trifuoroethylene (P(VDF-TrFE)), taking advantage of the synergies of the magnetostrictive filler and the piezoelectric polymer. The porous films show a piezoelectric response with an effective d33 coefficient of -22 pC/N-1, a maximum magnetization of 12 emu.g-1 and a maximum magnetoelectric coefficient of 9 mV.cm-1.Oe-1. In this way, a multifunctional membrane has been developed suitable for advanced applications ranging from biomedical to water treatment.