Máquina-ferramenta CNC para gravação: desenvolvimento de protótipo de baixo-custo

Dissertação de mestrado em Engenharia Mecatrónica

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

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.

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.

Ontology-based representation and generation of workflows for micro-task human-machine computation

Doctoral Program in Computer Science

Skin-derived cell-sheets as powerful tools to engineer skin analogues

Cell/cell-extracellular matrix (ECM) dynamic interactions appear to have a major role in regulating communication through soluble signaling, directing cell binding and activating substrates that participate in the highly organized wound healing process. Moreover, these interactions are also crucial for in vitro mimicking cutaneous physiology. Herein we explore cell sheet (CS) engineering to create cellular constructs formed by keratinocytes (hKC), fibroblasts (hDFB) and dermal microvascular endothelial cells (hDMEC), to target skin wound healing but also the in vitro recreation of relevant models. Taking advantage of temperature-responsive culture surfaces, which allow harvesting cultured cells as intact sheets along with the deposited native ECM, varied combinations of homotypic and heterotypic three-dimensional (3-D) CS-based constructs were developed. Constructs combining one CS of keratinocytes as an epidermis-like layer plus a vascularized dermis composed by hDFB and hDMECs were assembled as skin analogues for advancing in vitro testing. Simultaneously both hKC and hDMEC were shown to significantly contribute to the re-epithelialization of full-thickness mice skin wounds by promoting an early epithelial coverage, while hDMEC significantly lead to increased vessels density, incorporating the neovasculature. Thus, although determined by the cellular nature of the constructs, these outcomes demonstrated that CS engineering appear as an unique technology that open the possibility to create numerous combinations of 3D constructs to target defective wound healing as well as the construction of in vitro models to further mimic cutaneous functions crucial for drug screening and cosmetic testing assays.

Comparing standard and low-cost tools for gradient evaluation along potential cycling paths

Promoting the use of non-motorized modes of transport, such as cycling, is an important contribution to the improvement of mobility, accessibility and equity in cities. Cycling offers a fast and cheap transportation option for short distances, helping to lower pollutant emissions and contributing to a healthier way of life. In order to make the cycling mode more competitive in relation to motorized traffic, it is necessary to evaluate the potential of alternatives from the perspective of the physical effort. One way to do so consists of assessing the suitability of locations for implementing cycling infrastructures. In this work, four tools to determine the gradient along potential cycling paths are compared. Furthermore, an evaluation of the reliability of some low-cost tools to measure this parameter was conducted, by comparison with standard measurements using cartographic plans, on a field case study applied to the city of Braga, Portugal. These tools revealed a good level of accuracy for the planning stage, but proved to be less reliable for use in design.

Affordable prefabricated modular houses using cement and polymer based materials and advanced design tools

By taking advantage of the appropriate use of cement and polymer based materials and advanced computational tools, a pre-fabricated affordable house was built in a modular system. Modular system refers to the complete structure that is built-up by assembling pre-fabricated sandwich panels composed of steel fibre reinforced self-compacting concrete (SFRSCC) outer layers that are connected by innovative glass fibre reinforced polymer (GFRP) connectors, resulting in a panel with adequate structural, acoustic, and thermal insulation properties. The modular house was prepared for a typical family of six members, but its living area can be easily increased by assembling other pre-fabricated elements. The speed of construction and the cost of the constructive elements make these houses competitive when compared to traditional solutions. In this paper the relevant research subjacent to this project (LEGOUSE) is briefly described, as well as the construction process of the built real scale prototype.

The human eye as human-machine interface

Eye tracking as an interface to operate a computer is under research for a while and new systems are still being developed nowadays that provide some encouragement to those bound to illnesses that incapacitates them to use any other form of interaction with a computer. Although using computer vision processing and a camera, these systems are usually based on head mount technology being considered a contact type system. This paper describes the implementation of a human-computer interface based on a fully non-contact eye tracking vision system in order to allow people with tetraplegia to interface with a computer. As an assistive technology, a graphical user interface with special features was developed including a virtual keyboard to allow user communication, fast access to pre-stored phrases and multimedia and even internet browsing. This system was developed with the focus on low cost, user friendly functionality and user independency and autonomy.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

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.

Process simulation support in BPM tools: The case of BPMN

Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

Estudo do trabalho numa empresa de produção de pneus e implementação de ferramentas Lean

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering