UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)

In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in -carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis--carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.

Photoactivation of butyric acid from 6-aminobenzocoumarin cages

A new benzocoumarin bearing an amino group is proposed as a photocleavable protecting group for carboxylic acids. The novel heterocycle, 6-amino-4-chloromethyl-2-oxo-2H-naphtho[1,2-b]pyran was used in the preparation of ester conjugates of butyric acid, and of the corresponding mono- and di-methylated or ethylated derivatives. The photolability of the ester conjugates was studied by irradiation at selected wavelengths in methanol/HEPES buffer (80:20) solutions, and the release of butyric acid was followed with HPLC/UV and 1H NMR monitoring. Release of the carboxylic acid was faster for the monoalkylated derivatives (approximately within 20 min), at the longer wavelengths of irradiation (350 and 419 nm). The photophysics of the heterocyclic conjugates was also evaluated by both steady state and time-resolved methods.

Pró-fármacos fotoativáveis do péptido AAPV: síntese e avaliação da libertação controlada por luz

Dissertação de mestrado em Bioquímica Aplicada (área de especialização em Biomedicina)

Simultaneous detection of cyclopiazonic acid and aflatoxin B1 by HPLC in methanol/water mobile phase

A simple procedure for the simultaneous detection of cyclopiazonic acid (CPA) and aflatoxin B1 from fungal extracts is presented, using a methanol and water mobile phase and fluorescence detection. This methodology has been tested with standard solutions of both mycotoxins CPA and Aflatoxin B1 and with methanolic extracts of Aspergillus section Flavi strains, previously characterized for their mycotoxin production profile. Previously available methodology required the use of two different chromatographic runs for these mycotoxins, with distinct columns and detectors (fluorescence detection with a post-column photochemical derivatization (PHRED) for aflatoxin B1 and UV detection for CPA). The proposed method detects both mycotoxins in a single run. Data from these assays will be presented and discussed.

Implementação e validação de um método analítico para a determinação de sucralose (E955) em refrigerantes e cervejas por HPLC-ELSD

Dissertação de mestrado em Técnicas de Caraterização e Análise Química

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

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.

A systematic approach for externalities in occupational safety through the use of the delphi methodology

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.

Methodology for real-time adaptation of tunnels support using the observational method

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.

Effect of butadiene/styrene ratio, block structure and carbon nanotube content on the mechanical and electrical properties of thermoplastic elastomers after UV ageing

Thermoplastic elastomers based on a triblock copolymer styrene-butadiene-styrene (SBS) with different butadiene/styrene ratios, block structure and carbon nanotube (CNT) content were submitted to accelerated weathering in a Xenontest set up, in order to evaluate their stability to UV ageing. It was concluded that ageing mainly depends on butadiene/styrene ratio and block structure, with radial block structures exhibiting a faster ageing than linear block structures. Moreover, the presence of carbon nanotubes in the SBS copolymer slows down the ageing of the copolymer. The evaluation of the influence of ageing on the mechanical and electrical properties demonstrates that the mechanical degradation is higher for the C401 sample, which is the SBS sample with the largest butadiene content and a radial block structure. On the other hand, a copolymer derivate from SBS, the styrene-ethylene/butadiene-styrene (SEBS) sample, retains a maximum deformation of ~1000% after 80 h of accelerated ageing. The hydrophobicity of the samples decreases with increasing ageing time, the effect being larger for the samples with higher butadiene content. It is also verified that cytotoxicity increases with increasing UV ageing with the exception of SEBS, which remains not cytotoxic up to 80 h of accelerated ageing time, demonstrating its potential for applications involving exposition to environmental conditions.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Development of a methodology to incorporate risk and uncertainty in electricity power planning

Dissertação de mestrado em Engenharia Industrial

Microscopy- or DNA-based analyses: Which methodology gives a truer picture of stream-dwelling decomposer fungal diversity?

We assessed aquatic hyphomycete diversity in autumn and spring on oak leaves decomposing in five streams along a gradient of eutrophication in the Northwest of Portugal. Diversity was assessed through microscopy-based (identification by spore morphology) and DNA-based techniques (Denaturing Gradient Gel Electrophoresis and 454 pyrosequencing). Pyrosequencing revealed five times greater diversity than DGGE. About 21% of all aquatic hyphomycete species were exclusively detected by pyrosequencing and 26% exclusively by spore identification. In some streams, more than half of the recorded species would have remained undetected if we had relied only on spore identification. Nevertheless, in spring aquatic hyphomycete diversity was higher based on spore identification, probably because many species occurring in this season are not yet connected to ITS barcodes in genetic databases. Pyrosequencing was a powerful tool for revealing aquatic hyphomycete diversity on decomposing plant litter in streams and we strongly encourage researchers to continue the effort in barcoding fungal species.

Libertação fotocontrolada de moléculas bioativas a partir de conjugados de cumarinas

Dissertação de mestrado em Química Medicinal

Sustainability assessment of envelope wall solutions using MAXergy methodology

Projeto de investigação integrado de International Master in Sustainable Built Environment

O estudo da aplicação de acabamentos funcionais de barreira UV em fibras previamente ativadas por plasma

Tese de Doutoramento Engenharia Têxtil