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.

Neurocognitive profile and cognitive intervention in Alzheimer's disease

Tese de Doutoramento em Psicologia (Especialidade de Psicologia Clínica)

Electric vehicle assistant based in driver profile

This paper presents the outcomes of a research work consisting in the development of an Electric Vehicle Assistant (EVA), which creates and stores a driver profile where are contained the driving behaviours related with the EV energy consumption, the EV battery charging information, and the performed routes. This is an application for mobile devices that is able to passively track the driver behaviour and to access several information related with the EV in real time. It is also proposed a range prediction approach based on probability to take into account unpredictable effects of personal driving style, traffic or weather.

A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools

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.

Industrial engineering and management curriculum profile: Developing a framework of competences

This paper presents a framework of competences developed for Industrial Engineering and Management that can be used as a tool for curriculum analysis and design, including the teaching and learning processes as well as the alignment of the curriculum with the professional profile. The framework was applied to the Industrial Engineering and Management program at University of Minho (UMinho), Portugal, and it provides an overview of the connection between IEM knowledge areas and the competences defined in its curriculum. The framework of competences was developed through a process of analysis using a combination of methods and sources for data collection. The framework was developed according to four main steps: 1) characterization of IEM knowledge areas; 2) definition of IEM competences; 3) survey; 4) application of the framework at the IEM curriculum. The findings showed that the framework is useful to build an integrated vision of the curriculum. The most visible aspect in the learning outcomes of IEM program is the lack of balance between technical and transversal competences. There was not almost any reference to the transversal competences and it is fundamentally concentrated on Project-Based Learning courses. The framework presented in this paper provides a contribution to the definition of IEM professional profile through a set of competences which need to be explored further. In addition, it may be a relevant tool for IEM curriculum analysis and a contribution for bridging the gap between universities and companies.

Using the GPU to design complex profile extrusion dies

In the present work the benefits of using graphics processing units (GPU) to aid the design of complex geometry profile extrusion dies, are studied. For that purpose, a3Dfinite volume based code that employs unstructured meshes to solve and couple the continuity, momentum and energy conservation equations governing the fluid flow, together with aconstitutive equation, was used. To evaluate the possibility of reducing the calculation time spent on the numerical calculations, the numerical code was parallelized in the GPU, using asimple programing approach without complex memory manipulations. For verificationpurposes, simulations were performed for three benchmark problems: Poiseuille flow, lid-driven cavity flow and flow around acylinder. Subsequently, the code was used on the design of two real life extrusion dies for the production of a medical catheter and a wood plastic composite decking profile. To evaluate the benefits, the results obtained with the GPU parallelized code were compared, in terms of speedup, with a serial implementation of the same code, that traditionally runs on the central processing unit (CPU). The results obtained show that, even with the simple parallelization approach employed, it was possible to obtain a significant reduction of the computation times.

Innovative methodologies for the enhancement of the flexural strengthening performance of NSM CFRP technique for RC beams

Tese de Doutoramento em Engenharia Civil

Development of a new 3D OpenFOAM® solver to model the cooling stage in profile extrusion

[Excerpt] The advantages resulting from the use of numerical modelling tools to support the design of processing equipment are almost consensual. The design of calibration systems in profile extrusion is not an exception . H owever , the complex geome tries and heat exchange phenomena involved in this process require the use of numerical solvers able to model the heat exchange in more than one domain ( calibrator and polymer), the compatibilization of the heat transfer at the profile - calibrator interface and with the ability to deal with complex geometries. The combination of all these features is usually hard to find in commercial software. Moreover , the dimension of the meshes required to ob tain accurate results, result in computational times prohibitive for industrial application. (...)

Using OpenFOAM to aid the design of complex profile extrusion dies

[Extrat] Thermoplastic profiles are very attractive due to their inherent design freedom. However, the usual methodologies employed to design extrusion forming tools, based on experimental based trial–and–error procedures, are highly dependent on the designer’s experience and lead to high resources consumption. Despite of the relatively low cost of the raw materials employed on the production of this type of profiles, the resources involved in the die design process significantly increase their cost. These difficulties are even more evident when a complex geometry profile has to be produced and there is no previous experience with similar geometries. Therefore, novel design approaches are required, in order to reduce the required resources and guarantee a good performance for the produced profile. (...)

One-step in situ synthesis of polyamide microcapsules with inorganic payload and their transformation into responsive thermoplastic composite materials

Well-dispersed loads of finely powdered metals, metal oxides, several carbon allotropes or nanoclays are incorporated into highly porous polyamide 6 microcapsules in controllable amounts via an original one-step in situ fabrication technique. It is based on activated anionic polymerization (AAP) of ε-caprolactam in a hydrocarbon solvent performed in the presence of the respective micro- or nanosized loads. The forming microcapsules with typical diameters of 25-50 µm entrap up to 40 wt% of load. Their melt processing produces hybrid thermoplastic composites. Mechanical, electric conductivity and magnetic response measurements show that transforming of in situ loaded microcapsules into composites by melt processing (MP) is a facile and rapid method to fabricate materials with high mechanical resistance and electro-magnetic characteristics sufficient for many industrial applications. This novel concept requires low polymerization temperatures, no functionalization or compatibilization of the loads and it is easy to scale up at industrial production levels.

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.

Changes in peripheral refractive profile after orthokeratology for different degrees of myopia

Purpose: The purpose of this study was to evaluate the effect of orthokeratology for different degrees of myopia correction in the relative location of tangential (FT) and sagittal (FS) power errors across the central 70 of the visual field in the horizontal meridian. Methods: Thirty-four right eyes of 34 patients with a mean age of 25.2 ± 6.4 years were fitted with Paragon CRT (Mesa, AZ) rigid gas permeable contact lenses to treat myopia (2.15 ± 1.26D, range: 0.88 to 5.25D). Axial and peripheral refraction were measured along the central 70 of the horizontal visual field with the Grand Seiko WAM5500 open-field auto-refractor. Spherical equivalent (M), as well as tangential (FT) and sagittal power errors (FS) were obtained. Analysis was stratified in three groups according to baseline spherical equivalent: Group 1 [MBaseline = 0.88 to 1.50D; n = 11], Group 2 [MBaseline = 1.51 to 2.49D; n = 11], and Group 3 [MBaseline = 2.50 to 5.25D; n = 12]. Results: Spherical equivalent was significantly more myopic after treatment beyond the central 40 of the visual field (p50.001). FT became significantly more myopic for all groups in the nasal and temporal retina with 25 (p 0.017), 30 (p 0.007) and 35 (p 0.004) of eye rotation. Myopic change in FS was less consistent, achieving only statistical significance for all groups at 35 in the nasal and temporal retina (p 0.045). Conclusions: Orthokeratology changes significantly FT in the myopic direction beyond the central 40 of the visual field for all degrees of myopia. Changes induced by orthokeratology in relative peripheral M, FT and FS with 35 of eye rotation were significantly correlated with axial myopia at baseline. Keywords: Field

Women’s perception of separation/divorce in Portugal: A sociodemographic profile

This article focuses on the personal experiences of Portuguese women regarding separation and divorce. The sample included 96 women, with at least 1 child, who responded to an inventory that addressed conflict, dysfunctional conjugality, emotional experiences, social support, and adaptation to divorce. Higher levels of conflict and marital dysfunction in litigious divorces were found, as well as more conflict when different lawyers were employed. Those women who were satisfied with alimony and visiting rights reported less conflict, fewer negative emotional experiences, and greater social support. Level of education and duration of separation influenced women’s perceptions. Implications for intervention are addressed.

Comparing different methods to measure biofilm thickness: the techniques are: optical coherence tomography, confocal laser scanning microscopy and low load compression test

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Assessment of innovative solutions for non-load bearing masonry enclosures

This paper presents some of the results of the research project “Masonry Enclosures” developed in the framework of the transnational access (TA) to LNEC’s triaxial shake table within the FP7 project SERIES.